fix(ai): store chatContextWindow as a JSON number, not a ::text string

chatContextWindow (#189) is the first numeric provider field routed
through WorkspaceRepo.updateAiProviderSettings, whose patch builder cast
every value as `${v}::text`. The DTO validates it as @IsInt(), so a JS
number 200000 was stored as the JSON STRING "200000". The client guards
require `typeof === "number"` (ai-chat-window.tsx, context-badge.tsx),
so the `/ max` badge denominator never rendered and the whole feature
silently no-opped.

Branch the jsonb_build_object value cast by JS runtime type: numbers ->
::numeric (real JSON number), booleans -> ::boolean, everything else ->
::text (unchanged for the existing string fields). This is the root fix
(store as a real number) rather than coercing on read, so every reader
sees the correct type.

Add a DB round-trip int-spec asserting
jsonb_typeof(settings->'ai'->'provider'->'chatContextWindow') = 'number'
and that the value re-reads as the number 200000, including the
partial-merge path. CHANGELOG: Added entry for the chatContextWindow
setting and a Changed entry for the badge's new "used / max" meaning.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

CHANGELOG.md

@@ -12,13 +12,6 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Added
 
-- **Inline "Test" button per external MCP server.** Each server row in admin AI
-  settings now has its own "Test" button that runs an isolated connection check:
-  idle `Test` → green `OK · N` (with a tooltip listing the discovered tools, or
-  "No tools available") on success, or red `Failed` (tooltip with the sanitized
-  error) on a connection problem. State is per-row, so testing one server never
-  spins or recolours the others. (#170)
-
 - **Persistent AI-chat history as the source of truth + server-side export.**
   An assistant turn is now persisted to the database step by step: the row is
   inserted upfront as `streaming` and updated as each agent step finishes, then
@@ -50,6 +43,13 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
   OpenRouter, etc.; `openai` uses the official provider (real-OpenAI
   reasoning-model request shaping). Chosen explicitly rather than inferred from
   the base URL, since a custom URL can front real OpenAI too. (#175, #177)
+- **AI chat "Context window (tokens)" setting (`chatContextWindow`).** A new
+  admin field in AI settings that records the chat model's context-window size.
+  When set (> 0) it becomes the denominator of the header context-badge, which
+  now reads "used / max"; `0`/empty clears the limit and the badge shows only
+  the current context as before. There is no provider-independent way to read a
+  model's window automatically, so it is an explicit workspace-level value.
+  (#189)
 - **Per-MCP-server instructions in the agent prompt.** Each external MCP server
   now has an admin-authored `instructions` field ("how/when to use this server's
   tools") that is injected into the agent's system prompt next to that server's
@@ -68,6 +68,12 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
   model's reasoning out of the box. An endpoint that is real OpenAI behind a
   custom base URL should set the new `chatApiStyle` "Protocol" to `openai`. (#177)
 
+- **AI chat header context-badge now shows "used / max".** When an admin sets
+  the new `chatContextWindow`, the badge displays the current context size over
+  the configured window (e.g. `120k / 200k`) instead of switching to a live
+  per-turn token counter during streaming. With no window configured the badge
+  keeps showing just the current context. (#189)
+
 - **Footnotes now reuse (Pandoc semantics).** Multiple `[^a]` references to the
   same id are ONE footnote — one number, one definition, several back-references
   — instead of being renamed to `a__2`, `a__3`. Duplicate `[^a]:` definitions are

apps/client/public/locales/en-US/translation.json

@@ -713,8 +713,6 @@
   "Optional. Leave empty to allow all tools the server exposes.": "Optional. Leave empty to allow all tools the server exposes.",
   "Optional guidance for the agent on how and when to use this server's tools. Injected into the system prompt. The server's tools are namespaced as \"<server name>_*\".": "Optional guidance for the agent on how and when to use this server's tools. Injected into the system prompt. The server's tools are namespaced as \"<server name>_*\".",
   "Test": "Test",
-  "Failed": "Failed",
-  "OK · {{count}}": "OK · {{count}}",
   "Available tools": "Available tools",
   "No tools available": "No tools available",
   "Created successfully": "Created successfully",
@@ -1170,7 +1168,10 @@
   "Built-in assistant persona": "Built-in assistant persona",
   "Minimize": "Minimize",
   "Current context size": "Current context size",
-  "Tokens generated this turn": "Tokens generated this turn",
+  "Context size / model limit": "Context size / model limit",
+  "Context window (tokens)": "Context window (tokens)",
+  "Shows used / total in the chat header badge; empty hides the total.": "Shows used / total in the chat header badge; empty hides the total.",
+  "e.g. 200000": "e.g. 200000",
   "AI agent": "AI agent",
   "Take a look at the current document": "Take a look at the current document",
   "AI agent is typing…": "AI agent is typing…",

apps/client/public/locales/ru-RU/translation.json

@@ -705,7 +705,10 @@
   "Copy chat": "Копировать чат",
   "Created successfully": "Успешно создано",
   "Current context size": "Текущий размер контекста",
-  "Tokens generated this turn": "Токенов сгенерировано за ход",
+  "Context size / model limit": "Размер контекста / лимит модели",
+  "Context window (tokens)": "Размер окна контекста (токены)",
+  "Shows used / total in the chat header badge; empty hides the total.": "Показывает использовано/всего в шапке чата; пусто — скрыть лимит.",
+  "e.g. 200000": "напр. 200000",
   "Delete this chat?": "Удалить этот чат?",
   "Deleted successfully": "Успешно удалено",
   "Edited by AI agent on behalf of {{name}}": "Отредактировано AI-агентом от имени {{name}}",
@@ -1169,9 +1172,5 @@
   "Protocol": "Протокол",
   "How chat requests are sent and how reasoning is surfaced": "Как отправляются запросы чата и как показывается reasoning",
   "OpenAI-compatible (surfaces reasoning)": "OpenAI-совместимый (показывает reasoning)",
-  "OpenAI (official)": "OpenAI (официальный)",
-  "Test": "Тест",
-  "Failed": "Ошибка",
-  "OK · {{count}}": "OK · {{count}}",
-  "No tools available": "Нет доступных инструментов"
+  "OpenAI (official)": "OpenAI (официальный)"
 }

apps/client/src/features/ai-chat/components/ai-chat-window.tsx

@@ -6,7 +6,7 @@ import {
   useRef,
   useState,
 } from "react";
-import { Group, Loader, Tooltip } from "@mantine/core";
+import { Group, Loader } from "@mantine/core";
 import {
   IconArrowsDiagonal,
   IconCheck,
@@ -39,6 +39,7 @@ import {
 } from "@/features/ai-chat/queries/ai-chat-query.ts";
 import ConversationList from "@/features/ai-chat/components/conversation-list.tsx";
 import ChatThread from "@/features/ai-chat/components/chat-thread.tsx";
+import { ContextBadge } from "@/features/ai-chat/components/context-badge.tsx";
 import { exportAiChat } from "@/features/ai-chat/services/ai-chat-service.ts";
 import { useChatSession } from "@/features/ai-chat/hooks/use-chat-session.ts";
 import {
@@ -60,13 +61,6 @@ const MIN_HEIGHT = 400;
 // Margin kept between the window and the viewport edges while dragging.
 const EDGE_MARGIN = 8;
 
-/** Compact token formatter: 1.2M / 3.4k / 950. */
-function formatTokens(n: number): string {
-  if (n >= 1_000_000) return `${(n / 1_000_000).toFixed(1)}M`;
-  if (n >= 1_000) return `${(n / 1_000).toFixed(1)}k`;
-  return String(n);
-}
-
 // Compute the initial top-right placement at the default size, fitted to the
 // current viewport. Reads `window` only when called (inside an effect).
 function computeInitialGeom() {
@@ -161,12 +155,6 @@ export default function AiChatWindow() {
   const { data: messageRows, isLoading: messagesLoading } =
     useAiChatMessagesQuery(activeChatId ?? undefined);
 
-  // Live turn-token total (reasoning + output) for the in-flight turn, pushed up
-  // (THROTTLED to ~8 Hz inside ChatThread) so the header badge ticks mid-stream.
-  // `null` means no turn is in flight -> the badge falls back to the persisted
-  // context size below.
-  const [liveTurnTokens, setLiveTurnTokens] = useState<number | null>(null);
-
   // The page the user is currently viewing. AiChatWindow lives in a pathless
   // parent layout route, so useParams() can't see :pageSlug. Match the full
   // pathname against the authenticated page route instead so "the current page"
@@ -306,6 +294,21 @@ export default function AiChatWindow() {
     return 0;
   }, [activeChatId, messageRows]);
 
+  // The model's context-window size (badge denominator), read from the most
+  // recent assistant row that carries it. Admin-configured in AI settings and
+  // stamped onto the turn server-side, so it travels with the message metadata —
+  // no client-side model resolution, and it survives public shares / per-role
+  // models automatically. 0 (no limit configured, or older rows) → the badge
+  // hides the denominator and shows only the current context size.
+  const maxContextTokens = useMemo(() => {
+    if (!activeChatId || !messageRows) return 0;
+    for (let i = messageRows.length - 1; i >= 0; i--) {
+      const max = messageRows[i].metadata?.maxContextTokens;
+      if (typeof max === "number" && max > 0) return max;
+    }
+    return 0;
+  }, [activeChatId, messageRows]);
+
   // On (re)open, settle the geometry before paint (useLayoutEffect → no
   // first-frame jump): compute an initial top-right placement the first time,
   // and re-clamp an existing geometry to the current viewport on later opens
@@ -495,23 +498,14 @@ export default function AiChatWindow() {
         )}
 
         <div style={{ flex: 1, display: "flex", justifyContent: "center" }}>
-          {/* While a turn streams, show the LIVE turn-token count (ticks ~8 Hz);
-              once it finishes, fall back to the persisted context size. Require
-              > 0 so the very first emit (an empty tail message, count 0) does not
-              flash a "0" badge before any token streams in (#151 review). */}
-          {liveTurnTokens !== null && liveTurnTokens > 0 ? (
-            <Tooltip label={t("Tokens generated this turn")} withArrow>
-              <span className={classes.badge}>
-                {formatTokens(liveTurnTokens)}
-              </span>
-            </Tooltip>
-          ) : contextTokens > 0 ? (
-            <Tooltip label={t("Current context size")} withArrow>
-              <span className={classes.badge}>
-                {formatTokens(contextTokens)}
-              </span>
-            </Tooltip>
-          ) : null}
+          {/* Context badge: always "current / max" context size (or just current
+              when no model limit is configured). It no longer flips to a live
+              per-turn generation counter mid-stream — that live feedback lives in
+              the chat body's "Thinking · N tokens" block. */}
+          <ContextBadge
+            contextTokens={contextTokens}
+            maxContextTokens={maxContextTokens}
+          />
         </div>
 
         <div style={{ display: "flex", alignItems: "center", gap: 1 }}>
@@ -634,7 +628,6 @@ export default function AiChatWindow() {
               assistantName={currentRole?.name}
               onTurnFinished={onTurnFinished}
               onServerChatId={onServerChatId}
-              onLiveTurnTokens={setLiveTurnTokens}
             />
           )}
         </div>

apps/client/src/features/ai-chat/components/chat-thread.tsx

@@ -20,7 +20,6 @@ import {
 } from "@/features/ai-chat/utils/role-launch.ts";
 import { describeChatError } from "@/features/ai-chat/utils/error-message.ts";
 import { extractServerChatId } from "@/features/ai-chat/utils/adopt-chat-id.ts";
-import { liveTurnTokens } from "@/features/ai-chat/utils/count-stream-tokens.ts";
 import {
   dequeue,
   enqueueMessage,
@@ -67,12 +66,6 @@ interface ChatThreadProps {
    *  Copy/export button available mid-stream). Distinct from onTurnFinished,
    *  which fires only at the terminal outcome. */
   onServerChatId?: (serverChatId?: string) => void;
-  /** Reports the live turn-token total (reasoning + output) for the in-flight
-   *  turn so the parent can show a header badge that ticks mid-stream. THROTTLED
-   *  here (~8 Hz) so the parent re-renders a handful of times a second, not on
-   *  every streamed delta. Called with `null` when no turn is in flight (the
-   *  parent then reverts the badge to the persisted context size). */
-  onLiveTurnTokens?: (tokens: number | null) => void;
 }
 
 /**
@@ -117,7 +110,6 @@ export default function ChatThread({
   assistantName,
   onTurnFinished,
   onServerChatId,
-  onLiveTurnTokens,
 }: ChatThreadProps) {
   const { t } = useTranslation();
 
@@ -328,53 +320,6 @@ export default function ChatThread({
   // the SAME on-screen banner text can be mirrored into the export (issue #160).
   const errorView = error ? describeChatError(error.message ?? "", t) : null;
 
-  // Report the live turn-token total to the parent header badge, THROTTLED to
-  // ~8 Hz so the parent re-renders a few times a second instead of on every
-  // streamed delta. The tail assistant message's reasoning+output (estimate while
-  // streaming, authoritative once a step reports usage) is the live figure. When
-  // the turn ends we emit a final exact value, then `null` so the parent reverts
-  // the badge to the persisted context size.
-  const lastEmitRef = useRef(0);
-  const emitTimerRef = useRef<ReturnType<typeof setTimeout> | null>(null);
-  useEffect(() => {
-    if (!onLiveTurnTokens) return;
-    if (!isStreaming) {
-      // Turn ended (or never started): clear any pending throttle and revert.
-      if (emitTimerRef.current) {
-        clearTimeout(emitTimerRef.current);
-        emitTimerRef.current = null;
-      }
-      lastEmitRef.current = 0;
-      onLiveTurnTokens(null);
-      return;
-    }
-    const tail = messages[messages.length - 1];
-    const live = tail?.role === "assistant" ? liveTurnTokens(tail) : null;
-    const total = live ? live.reasoning + live.output : 0;
-    const now = Date.now();
-    const MIN_INTERVAL = 120; // ms (~8 Hz)
-    const elapsed = now - lastEmitRef.current;
-    if (elapsed >= MIN_INTERVAL) {
-      lastEmitRef.current = now;
-      onLiveTurnTokens(total);
-    } else if (!emitTimerRef.current) {
-      // Schedule a trailing emit so the FINAL value of a burst is not dropped.
-      emitTimerRef.current = setTimeout(() => {
-        emitTimerRef.current = null;
-        lastEmitRef.current = Date.now();
-        onLiveTurnTokens(total);
-      }, MIN_INTERVAL - elapsed);
-    }
-  }, [messages, isStreaming, onLiveTurnTokens]);
-
-  // Clear any pending throttle timer on unmount (chat switch via `key`) so a
-  // trailing emit can't fire into a torn-down thread's parent.
-  useEffect(() => {
-    return () => {
-      if (emitTimerRef.current) clearTimeout(emitTimerRef.current);
-    };
-  }, []);
-
   // A role was picked with autoStart=false: the role is bound but NOTHING was
   // sent, so chatId stays null and the empty state would keep showing the cards.
   // This flag hides the cards and reveals the composer (with the role indicated)

apps/client/src/features/ai-chat/components/context-badge.test.tsx

@@ -0,0 +1,69 @@
+import { describe, it, expect } from "vitest";
+import { render, screen, fireEvent } from "@testing-library/react";
+import { MantineProvider } from "@mantine/core";
+import { ContextBadge, formatTokens } from "./context-badge";
+
+// matchMedia (read by MantineProvider) is stubbed globally in vitest.setup.ts.
+// Without an I18nextProvider, `t(key)` returns the key verbatim, so tooltip
+// labels assert against their English source strings.
+
+function renderBadge(props: {
+  contextTokens: number;
+  maxContextTokens?: number;
+}) {
+  return render(
+    <MantineProvider>
+      <ContextBadge {...props} />
+    </MantineProvider>,
+  );
+}
+
+describe("formatTokens", () => {
+  it("formats with k / M suffixes", () => {
+    expect(formatTokens(572)).toBe("572");
+    expect(formatTokens(200_000)).toBe("200.0k");
+    expect(formatTokens(1_500_000)).toBe("1.5M");
+  });
+});
+
+describe("ContextBadge", () => {
+  it("shows `current / max` when a limit is configured", () => {
+    renderBadge({ contextTokens: 572, maxContextTokens: 200_000 });
+    expect(screen.getByText("572 / 200.0k")).toBeDefined();
+  });
+
+  it("shows only the current size when no limit is configured", () => {
+    renderBadge({ contextTokens: 572, maxContextTokens: 0 });
+    expect(screen.getByText("572")).toBeDefined();
+    // No denominator rendered.
+    expect(screen.queryByText(/\//)).toBeNull();
+  });
+
+  it("treats an undefined limit as no limit", () => {
+    renderBadge({ contextTokens: 1234 });
+    expect(screen.getByText("1.2k")).toBeDefined();
+    expect(screen.queryByText(/\//)).toBeNull();
+  });
+
+  it("renders nothing until there is a current context size", () => {
+    const { container } = renderBadge({
+      contextTokens: 0,
+      maxContextTokens: 200_000,
+    });
+    expect(container.querySelector("span")).toBeNull();
+  });
+
+  it("never flips to a live per-turn counter (no live mode); shows context as-is even above max", () => {
+    // `current > max` (estimate drift / smaller-model role) is shown unclamped.
+    renderBadge({ contextTokens: 210_000, maxContextTokens: 200_000 });
+    expect(screen.getByText("210.0k / 200.0k")).toBeDefined();
+  });
+
+  it("exposes the limit tooltip label on hover", async () => {
+    renderBadge({ contextTokens: 572, maxContextTokens: 200_000 });
+    fireEvent.mouseEnter(screen.getByText("572 / 200.0k"));
+    expect(
+      await screen.findByText("Context size / model limit"),
+    ).toBeDefined();
+  });
+});

apps/client/src/features/ai-chat/components/context-badge.tsx

@@ -0,0 +1,61 @@
+import { Tooltip } from "@mantine/core";
+import { useTranslation } from "react-i18next";
+import classes from "@/features/ai-chat/components/ai-chat-window.module.css";
+
+/** Compact token formatter: 1.2M / 3.4k / 950. */
+export function formatTokens(n: number): string {
+  if (n >= 1_000_000) return `${(n / 1_000_000).toFixed(1)}M`;
+  if (n >= 1_000) return `${(n / 1_000).toFixed(1)}k`;
+  return String(n);
+}
+
+interface ContextBadgeProps {
+  // Current context size for the active chat (tokens occupied in the model's
+  // window). 0 = unknown → nothing is rendered.
+  contextTokens: number;
+  // The model's context-window size (tokens), from AI settings. 0/undefined =
+  // no limit known → only the current size is shown (no denominator).
+  maxContextTokens?: number;
+}
+
+/**
+ * Header badge that ALWAYS shows the current context size, and — when the model's
+ * context-window size is configured — appends "/ max" so the badge reads
+ * "current / max" (e.g. `572 / 200k`). This is a single, stable meaning: unlike
+ * the previous design it never flips to a live per-turn generation counter while
+ * streaming (that live feedback lives in the chat body's "Thinking · N tokens").
+ *
+ * No limit configured (or older history rows without it) → the denominator is
+ * hidden and the badge shows the current size only, matching the prior at-rest
+ * behaviour. `context > max` (estimate drift, or a role on a smaller model) is
+ * shown as-is, without clamping.
+ */
+export function ContextBadge({
+  contextTokens,
+  maxContextTokens,
+}: ContextBadgeProps) {
+  const { t } = useTranslation();
+
+  // Nothing to show until the first persisted context figure exists.
+  if (!(contextTokens > 0)) return null;
+
+  const hasMax = typeof maxContextTokens === "number" && maxContextTokens > 0;
+  const label = hasMax
+    ? `${formatTokens(contextTokens)} / ${formatTokens(maxContextTokens)}`
+    : formatTokens(contextTokens);
+
+  return (
+    <Tooltip
+      label={
+        hasMax
+          ? t("Context size / model limit")
+          : t("Current context size")
+      }
+      withArrow
+    >
+      <span className={classes.badge}>{label}</span>
+    </Tooltip>
+  );
+}
+
+export default ContextBadge;

apps/client/src/features/ai-chat/types/ai-chat.types.ts

@@ -113,9 +113,14 @@ export interface IAiChatMessageRow {
     };
     // Current context size for the turn = final-step (input+output) tokens, i.e.
     // how much the conversation occupies in the model's context window after this
-    // turn. Distinct from `usage` (legacy cumulative totalUsage). Shown in the
-    // floating window's header badge.
+    // turn. Distinct from `usage` (legacy cumulative totalUsage). Shown as the
+    // numerator of the floating window's "current / max" header badge.
     contextTokens?: number;
+    // The model's context-window size (tokens), admin-configured in AI settings
+    // and stamped onto the turn server-side. The denominator of the header badge.
+    // Absent/0 (older rows, or no limit configured) → the badge hides the
+    // denominator and shows only the current context size (`contextTokens`).
+    maxContextTokens?: number;
     // Set on an assistant row whose turn ended in a provider/stream error; the
     // raw provider error text (e.g. "402: ...") for inline display in the thread.
     error?: string;

apps/client/src/features/ai-chat/utils/count-stream-tokens.test.ts

@@ -1,17 +1,5 @@
 import { describe, expect, it } from "vitest";
-import type { UIMessage } from "@ai-sdk/react";
-import {
-  estimateTokens,
-  liveTurnTokens,
-} from "@/features/ai-chat/utils/count-stream-tokens.ts";
-
-const msg = (parts: unknown[], metadata?: unknown): UIMessage =>
-  ({
-    id: Math.random().toString(),
-    role: "assistant",
-    parts,
-    metadata,
-  }) as UIMessage;
+import { estimateTokens } from "@/features/ai-chat/utils/count-stream-tokens.ts";
 
 describe("estimateTokens", () => {
   it("returns 0 for the empty string", () => {
@@ -25,147 +13,3 @@ describe("estimateTokens", () => {
     expect(estimateTokens("12345678")).toBe(2);
   });
 });
-
-describe("liveTurnTokens — estimate path", () => {
-  it("is all zeros for an undefined message", () => {
-    expect(liveTurnTokens(undefined)).toEqual({
-      reasoning: 0,
-      output: 0,
-      authoritative: false,
-    });
-  });
-
-  it("is all zeros for a parts-less message", () => {
-    expect(liveTurnTokens({ id: "x", role: "assistant" } as UIMessage)).toEqual({
-      reasoning: 0,
-      output: 0,
-      authoritative: false,
-    });
-  });
-
-  it("estimates output from text parts", () => {
-    // 8 chars -> 2 tokens.
-    const r = liveTurnTokens(msg([{ type: "text", text: "12345678" }]));
-    expect(r).toEqual({ reasoning: 0, output: 2, authoritative: false });
-  });
-
-  it("estimates reasoning from reasoning parts (kept separate from output)", () => {
-    const r = liveTurnTokens(
-      msg([
-        { type: "reasoning", text: "12345678" },
-        { type: "text", text: "abcd" },
-      ]),
-    );
-    expect(r).toEqual({ reasoning: 2, output: 1, authoritative: false });
-  });
-
-  it("accumulates across multiple text + reasoning parts (multi-step)", () => {
-    const r = liveTurnTokens(
-      msg([
-        { type: "reasoning", text: "abcd" }, // 1
-        { type: "text", text: "abcd" }, // 1
-        { type: "tool-getPage", state: "output-available" }, // ignored
-        { type: "reasoning", text: "abcd" }, // 1
-        { type: "text", text: "abcdefgh" }, // 2
-      ]),
-    );
-    expect(r).toEqual({ reasoning: 2, output: 3, authoritative: false });
-  });
-
-  it("ignores non text/reasoning parts (tools, step-start)", () => {
-    const r = liveTurnTokens(
-      msg([
-        { type: "step-start" },
-        { type: "tool-getPage", state: "input-available" },
-      ]),
-    );
-    expect(r).toEqual({ reasoning: 0, output: 0, authoritative: false });
-  });
-});
-
-describe("liveTurnTokens — authoritative path", () => {
-  it("returns authoritative usage verbatim, splitting reasoning out of output", () => {
-    // outputTokens INCLUDES reasoning in the AI SDK shape -> answer = 100 - 30.
-    const r = liveTurnTokens(
-      msg([{ type: "text", text: "estimate would be tiny" }], {
-        usage: { inputTokens: 500, outputTokens: 100, reasoningTokens: 30 },
-      }),
-    );
-    expect(r).toEqual({ reasoning: 30, output: 70, authoritative: true });
-  });
-
-  it("treats missing reasoningTokens as 0 and keeps full output", () => {
-    const r = liveTurnTokens(
-      msg([{ type: "text", text: "x" }], {
-        usage: { inputTokens: 10, outputTokens: 42 },
-      }),
-    );
-    expect(r).toEqual({ reasoning: 0, output: 42, authoritative: true });
-  });
-
-  it("never returns a negative output when reasoning exceeds reported output", () => {
-    const r = liveTurnTokens(
-      msg([], { usage: { outputTokens: 10, reasoningTokens: 40 } }),
-    );
-    expect(r).toEqual({ reasoning: 40, output: 0, authoritative: true });
-  });
-
-  it("falls back to the estimate when metadata has no usage object", () => {
-    const r = liveTurnTokens(
-      msg([{ type: "text", text: "abcd" }], { chatId: "c1" }),
-    );
-    expect(r).toEqual({ reasoning: 0, output: 1, authoritative: false });
-  });
-});
-
-describe("liveTurnTokens — combined authoritative + estimate (#163)", () => {
-  it("ticks the in-flight step above the completed-steps authoritative base", () => {
-    // The authoritative usage is the sum over COMPLETED steps (step 1). The
-    // CURRENT step is streaming and its text is NOT in `usage` yet, but it IS in
-    // the parts -> the running estimate must push the live figure above the base
-    // so the badge keeps growing between step boundaries.
-    const longText = "x".repeat(800); // 800 chars -> 200 est output tokens
-    const r = liveTurnTokens(
-      msg([{ type: "text", text: longText }], {
-        usage: { inputTokens: 500, outputTokens: 40 }, // step-1 base: 40 output
-      }),
-    );
-    // max(authOutput=40, estOutput=200) = 200 -> the counter ticks, not frozen.
-    expect(r.output).toBe(200);
-    expect(r.authoritative).toBe(true);
-  });
-
-  it("ticks reasoning of the in-flight step above the authoritative reasoning base", () => {
-    const longReasoning = "r".repeat(400); // 400 chars -> 100 est reasoning
-    const r = liveTurnTokens(
-      msg([{ type: "reasoning", text: longReasoning }], {
-        usage: { inputTokens: 100, outputTokens: 20, reasoningTokens: 20 },
-      }),
-    );
-    // reasoning: max(20, 100) = 100 ; output: max(max(0,20-20)=0, 0) = 0.
-    expect(r.reasoning).toBe(100);
-    expect(r.output).toBe(0);
-    expect(r.authoritative).toBe(true);
-  });
-
-  it("snaps to the authoritative figure once it exceeds the rough estimate", () => {
-    // Short on-screen text (estimate tiny) but a large authoritative output:
-    // the exact figure wins at the boundary (the counter never under-reports).
-    const r = liveTurnTokens(
-      msg([{ type: "text", text: "abcd" }], {
-        usage: { inputTokens: 10, outputTokens: 5000 },
-      }),
-    );
-    expect(r.output).toBe(5000);
-  });
-
-  it("is monotonic: max never drops below the authoritative base when the estimate is smaller", () => {
-    // Mirrors the legacy 'verbatim' tests: estimate < authoritative -> unchanged.
-    const r = liveTurnTokens(
-      msg([{ type: "text", text: "tiny" }], {
-        usage: { inputTokens: 500, outputTokens: 100, reasoningTokens: 30 },
-      }),
-    );
-    expect(r).toEqual({ reasoning: 30, output: 70, authoritative: true });
-  });
-});

apps/client/src/features/ai-chat/utils/count-stream-tokens.ts

@@ -1,18 +1,16 @@
-import type { UIMessage } from "@ai-sdk/react";
-
 /**
- * Live token counting for a streaming AI-chat turn — split into REASONING
- * (thinking) and OUTPUT (answer) tokens, mirroring how Claude Code shows
- * `Thinking… · 60 tokens` next to its thinking indicator.
+ * Live token ESTIMATION for a streaming AI-chat turn.
  *
  * No provider streams exact per-token usage mid-stream, so the live number is a
- * CLIENT ESTIMATE (chars/≈4 heuristic) that is reconciled to AUTHORITATIVE usage
- * once the server attaches it on a step/turn boundary (see the server's
- * `chatStreamMetadata` + the client's read of `message.metadata.usage`). When
- * authoritative usage is present we return it verbatim (the number "jumps to
- * exact"); otherwise we return the running estimate. Pure + unit-testable: it
- * never runs a real BPE tokenizer (that would be O(n²) on the hot path, bloat the
+ * CLIENT ESTIMATE (chars/≈4 heuristic). It powers the chat body's
+ * `Thinking… · N tokens` indicator (see `ReasoningBlock`), which reconciles to
+ * the authoritative server usage once it lands. Pure + unit-testable: it never
+ * runs a real BPE tokenizer (that would be O(n²) on the hot path, bloat the
  * bundle, and be wrong for Gemini/Ollama anyway).
+ *
+ * The former header-badge `liveTurnTokens()` split was removed with #189 (the
+ * header badge now shows the stable "current / max" context size, not a live
+ * per-turn counter); the live feedback remains in `ReasoningBlock`.
  */
 
 /**
@@ -24,90 +22,3 @@ export function estimateTokens(text: string): number {
   if (!text) return 0;
   return Math.ceil(text.length / 4);
 }
-
-/** Authoritative per-step/turn usage the server attaches to message metadata. */
-export interface AuthoritativeUsage {
-  inputTokens?: number;
-  outputTokens?: number;
-  totalTokens?: number;
-  reasoningTokens?: number;
-}
-
-/** Live token split for a turn's tail (streaming) assistant message. */
-export interface LiveTurnTokens {
-  /** Thinking/reasoning tokens (estimate, or authoritative when available). */
-  reasoning: number;
-  /** Answer/output tokens (estimate, or authoritative when available). */
-  output: number;
-  /** True when the numbers come from authoritative server usage, not estimate. */
-  authoritative: boolean;
-}
-
-/** Read the authoritative usage off a UIMessage's metadata, if the server set it. */
-function metadataUsage(message: UIMessage): AuthoritativeUsage | undefined {
-  const meta = message?.metadata as
-    | { usage?: AuthoritativeUsage }
-    | undefined;
-  const usage = meta?.usage;
-  if (!usage || typeof usage !== "object") return undefined;
-  return usage;
-}
-
-/**
- * Token split for the given (streaming) assistant message.
- *
- * COMBINES the authoritative server usage with the running text estimate so the
- * counter ticks in real time AND lands exact. The server only attaches
- * `metadata.usage` at a step/turn boundary (`finish-step`/`finish`) and it is
- * CUMULATIVE over COMPLETED steps — it does NOT yet include the in-flight step.
- * So a multi-step turn that returned the authoritative figure verbatim would
- * FREEZE between boundaries and jump in steps (issue #163).
- *
- * Instead we always compute the running ESTIMATE (chars/≈4 over the message's
- * `reasoning`/`text` parts, which grows on every streamed delta) and take the
- * per-component MAX of the authoritative base and the estimate:
- *   - between boundaries the estimate of the in-flight step ticks the number up;
- *   - at a boundary the authoritative figure snaps it to exact;
- *   - because the server's usage is cumulative and we only ever take the max, the
- *     number is MONOTONIC — it never drops.
- *
- * Providers that don't stream reasoning text still surface a reasoning count once
- * the authoritative usage arrives (`max(reasoningTokens, 0)`); on the pure
- * estimate path (no usage yet) such a turn shows `reasoning: 0` until then.
- */
-export function liveTurnTokens(message: UIMessage | undefined): LiveTurnTokens {
-  if (!message) return { reasoning: 0, output: 0, authoritative: false };
-
-  // Running ESTIMATE over every reasoning/text part — grows on each delta. This
-  // includes the IN-FLIGHT step, which the authoritative usage does not cover yet.
-  let estReasoning = 0;
-  let estOutput = 0;
-  for (const part of message.parts ?? []) {
-    if (part.type === "reasoning") {
-      estReasoning += estimateTokens((part as { text?: string }).text ?? "");
-    } else if (part.type === "text") {
-      estOutput += estimateTokens((part as { text?: string }).text ?? "");
-    }
-  }
-
-  const usage = metadataUsage(message);
-  if (!usage) {
-    // No authoritative usage streamed yet: the estimate IS the live figure.
-    return { reasoning: estReasoning, output: estOutput, authoritative: false };
-  }
-
-  // Authoritative sum over COMPLETED steps. `outputTokens` already INCLUDES
-  // reasoning in the AI SDK usage shape, so subtract it out for the "answer"
-  // figure (never go negative if a provider reports them inconsistently).
-  const authReasoning = usage.reasoningTokens ?? 0;
-  const authOutput = Math.max(0, (usage.outputTokens ?? 0) - authReasoning);
-
-  // Per-component max: the in-flight step's estimate ticks above the completed-
-  // steps base between boundaries, and the authoritative figure wins once it
-  // exceeds the (rough) estimate at the next boundary. Monotonic by construction.
-  return {
-    reasoning: Math.max(authReasoning, estReasoning),
-    output: Math.max(authOutput, estOutput),
-    authoritative: true,
-  };
-}

apps/client/src/features/workspace/components/settings/components/ai-mcp-server-row.test.tsx

@@ -1,204 +0,0 @@
-import { describe, it, expect, vi, beforeEach } from "vitest";
-import { render, screen, fireEvent, waitFor, within } from "@testing-library/react";
-import { MantineProvider } from "@mantine/core";
-import { QueryClient, QueryClientProvider } from "@tanstack/react-query";
-import { IAiMcpServer } from "@/features/workspace/services/ai-mcp-server-service.ts";
-
-// matchMedia (read by MantineProvider) is stubbed globally in vitest.setup.ts.
-
-// Stub react-i18next so `t` returns the key with `{{count}}` interpolated. This
-// keeps assertions on the row's OWN label logic, mirroring the t-mock pattern
-// used by other component tests in the repo.
-vi.mock("react-i18next", () => ({
-  useTranslation: () => ({
-    t: (key: string, opts?: { count?: number }) =>
-      opts && typeof opts.count === "number"
-        ? key.replace("{{count}}", String(opts.count))
-        : key,
-  }),
-}));
-
-// Mock only the network call. The REAL useTestAiMcpServerMutation runs on a real
-// QueryClient so each row gets a genuinely independent mutation instance — this
-// is exactly the isolation the feature relies on (#170).
-const testAiMcpServer = vi.fn();
-vi.mock("@/features/workspace/services/ai-mcp-server-service.ts", () => ({
-  testAiMcpServer: (id: string) => testAiMcpServer(id),
-}));
-
-import AiMcpServerRow from "./ai-mcp-server-row.tsx";
-
-const baseServer = (over?: Partial<IAiMcpServer>): IAiMcpServer => ({
-  id: "srv-1",
-  name: "Search",
-  transport: "http",
-  url: "https://example.com/mcp",
-  enabled: true,
-  toolAllowlist: null,
-  hasHeaders: false,
-  instructions: null,
-  ...over,
-});
-
-function tree(server: IAiMcpServer, testid: string) {
-  return (
-    <div data-testid={testid}>
-      <AiMcpServerRow
-        server={server}
-        onEdit={vi.fn()}
-        onDelete={vi.fn()}
-        onToggleEnabled={vi.fn()}
-      />
-    </div>
-  );
-}
-
-function renderRow(server: IAiMcpServer, testid: string) {
-  const client = new QueryClient({
-    defaultOptions: { mutations: { retry: false }, queries: { retry: false } },
-  });
-  const utils = render(
-    <QueryClientProvider client={client}>
-      <MantineProvider>{tree(server, testid)}</MantineProvider>
-    </QueryClientProvider>,
-  );
-  // A rerender helper that swaps only the server prop (same QueryClient, so the
-  // row keeps its mutation state and the reset-on-change effect is exercised).
-  const rerenderWith = (next: IAiMcpServer) =>
-    utils.rerender(
-      <QueryClientProvider client={client}>
-        <MantineProvider>{tree(next, testid)}</MantineProvider>
-      </QueryClientProvider>,
-    );
-  return { ...utils, rerenderWith };
-}
-
-describe("AiMcpServerRow — inline Test button", () => {
-  beforeEach(() => {
-    testAiMcpServer.mockReset();
-  });
-
-  it("starts in the idle state with a plain 'Test' label", () => {
-    renderRow(baseServer(), "row");
-    const row = screen.getByTestId("row");
-    expect(within(row).getByRole("button", { name: "Test" })).toBeDefined();
-  });
-
-  it("shows a green 'OK · N' label with the tool count on success", async () => {
-    testAiMcpServer.mockResolvedValue({ ok: true, tools: ["a", "b", "c"] });
-    renderRow(baseServer(), "row");
-    const row = screen.getByTestId("row");
-
-    fireEvent.click(within(row).getByRole("button", { name: "Test" }));
-
-    await waitFor(() =>
-      expect(within(row).getByRole("button", { name: /OK · 3/ })).toBeDefined(),
-    );
-  });
-
-  it("shows 'Failed' on a connection error", async () => {
-    testAiMcpServer.mockResolvedValue({ ok: false, error: "boom" });
-    renderRow(baseServer(), "row");
-    const row = screen.getByTestId("row");
-
-    fireEvent.click(within(row).getByRole("button", { name: "Test" }));
-
-    await waitFor(() =>
-      expect(within(row).getByRole("button", { name: "Failed" })).toBeDefined(),
-    );
-  });
-
-  it("shows 'Failed' when the request itself rejects (401/403/500/network)", async () => {
-    // A real reject yields no { ok:false } payload — the row must read isError,
-    // not just mutation.data, or it would spin then silently revert to "Test".
-    testAiMcpServer.mockRejectedValue(new Error("Request failed"));
-    renderRow(baseServer(), "row");
-    const row = screen.getByTestId("row");
-
-    fireEvent.click(within(row).getByRole("button", { name: "Test" }));
-
-    await waitFor(() =>
-      expect(within(row).getByRole("button", { name: "Failed" })).toBeDefined(),
-    );
-  });
-
-  it("shows 'OK · 0' and a 'No tools available' tooltip for an empty tool list", async () => {
-    testAiMcpServer.mockResolvedValue({ ok: true, tools: [] });
-    renderRow(baseServer(), "row");
-    const row = screen.getByTestId("row");
-
-    fireEvent.click(within(row).getByRole("button", { name: "Test" }));
-
-    await waitFor(() =>
-      expect(within(row).getByRole("button", { name: /OK · 0/ })).toBeDefined(),
-    );
-  });
-
-  it("resets a stale result when url / transport / hasHeaders change", async () => {
-    testAiMcpServer.mockResolvedValue({ ok: true, tools: ["a", "b", "c"] });
-    const { rerenderWith } = renderRow(baseServer(), "row");
-    const row = () => screen.getByTestId("row");
-
-    fireEvent.click(within(row()).getByRole("button", { name: "Test" }));
-    await waitFor(() =>
-      expect(within(row()).getByRole("button", { name: /OK · 3/ })).toBeDefined(),
-    );
-
-    // Changing the URL must drop the stale green result back to idle "Test".
-    rerenderWith(baseServer({ url: "https://changed.example.com/mcp" }));
-    await waitFor(() =>
-      expect(within(row()).getByRole("button", { name: "Test" })).toBeDefined(),
-    );
-
-    // Same for the transport.
-    fireEvent.click(within(row()).getByRole("button", { name: "Test" }));
-    await waitFor(() =>
-      expect(within(row()).getByRole("button", { name: /OK · 3/ })).toBeDefined(),
-    );
-    rerenderWith(
-      baseServer({ url: "https://changed.example.com/mcp", transport: "sse" }),
-    );
-    await waitFor(() =>
-      expect(within(row()).getByRole("button", { name: "Test" })).toBeDefined(),
-    );
-
-    // And for the presence of auth headers.
-    fireEvent.click(within(row()).getByRole("button", { name: "Test" }));
-    await waitFor(() =>
-      expect(within(row()).getByRole("button", { name: /OK · 3/ })).toBeDefined(),
-    );
-    rerenderWith(
-      baseServer({
-        url: "https://changed.example.com/mcp",
-        transport: "sse",
-        hasHeaders: true,
-      }),
-    );
-    await waitFor(() =>
-      expect(within(row()).getByRole("button", { name: "Test" })).toBeDefined(),
-    );
-  });
-
-  it("keeps each row's result isolated (testing one does not affect another)", async () => {
-    // Resolve based on id so the two rows get different outcomes.
-    testAiMcpServer.mockImplementation(async (id: string) =>
-      id === "ok-1"
-        ? { ok: true, tools: ["x", "y"] }
-        : { ok: false, error: "down" },
-    );
-
-    renderRow(baseServer({ id: "ok-1", name: "Good" }), "row-ok");
-    renderRow(baseServer({ id: "fail-1", name: "Bad" }), "row-fail");
-
-    const okRow = screen.getByTestId("row-ok");
-    fireEvent.click(within(okRow).getByRole("button", { name: "Test" }));
-
-    await waitFor(() =>
-      expect(within(okRow).getByRole("button", { name: /OK · 2/ })).toBeDefined(),
-    );
-
-    // The untouched row must still be idle — no shared/global pending state.
-    const failRow = screen.getByTestId("row-fail");
-    expect(within(failRow).getByRole("button", { name: "Test" })).toBeDefined();
-  });
-});

apps/client/src/features/workspace/components/settings/components/ai-mcp-server-row.tsx

@@ -1,161 +0,0 @@
-import { useEffect } from "react";
-import { ActionIcon, Badge, Button, Group, Stack, Switch, Text, Tooltip } from "@mantine/core";
-import {
-  IconCheck,
-  IconPencil,
-  IconPlugConnected,
-  IconTrash,
-  IconX,
-} from "@tabler/icons-react";
-import { useTranslation } from "react-i18next";
-import { useTestAiMcpServerMutation } from "@/features/workspace/queries/ai-mcp-server-query.ts";
-import { IAiMcpServer } from "@/features/workspace/services/ai-mcp-server-service.ts";
-
-interface AiMcpServerRowProps {
-  server: IAiMcpServer;
-  onEdit: (server: IAiMcpServer) => void;
-  onDelete: (server: IAiMcpServer) => void;
-  onToggleEnabled: (server: IAiMcpServer, enabled: boolean) => void;
-}
-
-/**
- * A single external MCP server row with an inline "Test" button. Each row owns
- * its OWN test mutation instance so the loading/result state is isolated per
- * row — a list-level mutation would make every row's spinner and colour jump on
- * any single test (#170).
- */
-export default function AiMcpServerRow({
-  server,
-  onEdit,
-  onDelete,
-  onToggleEnabled,
-}: AiMcpServerRowProps) {
-  const { t } = useTranslation();
-  const testMutation = useTestAiMcpServerMutation();
-
-  // The result colour/label reflects the connection params at the time of the
-  // test. The row is keyed by id and never remounts, so a stale "OK"/"Failed"
-  // would otherwise stick after the connection params change. Reset on those.
-  // Note: `hasHeaders` is a presence flag only (header values are write-only and
-  // never returned), so this resets on adding/removing auth headers, NOT on
-  // rotating a token's value — that value-only change is invisible to the client.
-  useEffect(() => {
-    testMutation.reset();
-    // eslint-disable-next-line react-hooks/exhaustive-deps
-  }, [server.url, server.transport, server.hasHeaders]);
-
-  const result = testMutation.data;
-
-  // Derive the button's appearance from the test outcome. Colour is never the
-  // only signal — the label changes too (a11y / colour-blind friendly).
-  let label = t("Test");
-  let color: string | undefined;
-  let variant = "default";
-  let icon = <IconPlugConnected size={16} />;
-  let tooltip: string | undefined;
-
-  if (result?.ok) {
-    label = t("OK · {{count}}", { count: result.tools.length });
-    color = "green";
-    variant = "light";
-    icon = <IconCheck size={16} />;
-    tooltip =
-      result.tools.length > 0
-        ? result.tools.join(", ")
-        : t("No tools available");
-  } else if (result && "error" in result) {
-    // Server-reported failure ({ ok: false, error }, HTTP 200). The error string
-    // is already sanitized server-side (no secrets). The `"error" in result`
-    // guard is required: `result?.ok` optional-chaining doesn't narrow the union
-    // in the else branch, so a bare `else if (result)` fails to type-check.
-    label = t("Failed");
-    color = "red";
-    variant = "light";
-    icon = <IconX size={16} />;
-    tooltip = result.error;
-  } else if (testMutation.isError) {
-    // The request itself rejected (401/403/500/network) — there is no result
-    // payload, so without this the row would silently revert to "Test".
-    label = t("Failed");
-    color = "red";
-    variant = "light";
-    icon = <IconX size={16} />;
-    tooltip =
-      testMutation.error?.["response"]?.data?.message ??
-      t("Failed to update data");
-  }
-
-  const testButton = (
-    <Button
-      size="xs"
-      variant={variant}
-      color={color}
-      // Fixed min-width so the row does not jump as the label changes
-      // (Test -> OK · 5 -> Failed).
-      miw={88}
-      leftSection={icon}
-      // Mantine disables the button automatically while loading.
-      loading={testMutation.isPending}
-      onClick={() => testMutation.mutate(server.id)}
-    >
-      {label}
-    </Button>
-  );
-
-  return (
-    <Group justify="space-between" wrap="nowrap">
-      <Stack gap={2} style={{ minWidth: 0 }}>
-        <Group gap="xs">
-          <Text fw={500} truncate>
-            {server.name}
-          </Text>
-          <Badge size="xs" variant="light">
-            {server.transport.toUpperCase()}
-          </Badge>
-        </Group>
-        <Text
-          size="xs"
-          c="dimmed"
-          truncate
-          style={{ fontFamily: "ui-monospace, Menlo, monospace" }}
-        >
-          {server.url}
-        </Text>
-      </Stack>
-
-      <Group gap="xs" wrap="nowrap">
-        {/* Show the tooltip (tools list / error) only once there is a result. */}
-        {tooltip ? (
-          <Tooltip label={tooltip} multiline maw={320} withArrow>
-            {testButton}
-          </Tooltip>
-        ) : (
-          testButton
-        )}
-        <Switch
-          size="sm"
-          checked={server.enabled}
-          aria-label={t("Enabled")}
-          onChange={(event) =>
-            onToggleEnabled(server, event.currentTarget.checked)
-          }
-        />
-        <ActionIcon
-          variant="subtle"
-          aria-label={t("Edit")}
-          onClick={() => onEdit(server)}
-        >
-          <IconPencil size={16} />
-        </ActionIcon>
-        <ActionIcon
-          variant="subtle"
-          color="red"
-          aria-label={t("Delete")}
-          onClick={() => onDelete(server)}
-        >
-          <IconTrash size={16} />
-        </ActionIcon>
-      </Group>
-    </Group>
-  );
-}

apps/client/src/features/workspace/components/settings/components/ai-mcp-servers.tsx

@@ -1,5 +1,6 @@
 import { useState } from "react";
 import {
+  ActionIcon,
   Badge,
   Box,
   Button,
@@ -7,11 +8,12 @@ import {
   Modal,
   Paper,
   Stack,
+  Switch,
   Text,
 } from "@mantine/core";
 import { useDisclosure } from "@mantine/hooks";
 import { modals } from "@mantine/modals";
-import { IconPlus } from "@tabler/icons-react";
+import { IconPencil, IconPlus, IconTrash } from "@tabler/icons-react";
 import { useTranslation } from "react-i18next";
 import useUserRole from "@/hooks/use-user-role.tsx";
 import {
@@ -21,7 +23,6 @@ import {
 } from "@/features/workspace/queries/ai-mcp-server-query.ts";
 import { IAiMcpServer } from "@/features/workspace/services/ai-mcp-server-service.ts";
 import AiMcpServerForm from "./ai-mcp-server-form.tsx";
-import AiMcpServerRow from "./ai-mcp-server-row.tsx";
 
 /**
  * Admin section: list / add / edit / delete external MCP servers the agent may
@@ -111,16 +112,55 @@ export default function AiMcpServers() {
 
       <Stack gap="xs" mt="sm">
         {servers?.map((server) => (
-          // Keyed by id (never remounts) so each row keeps its own test state.
-          <AiMcpServerRow
-            key={server.id}
-            server={server}
-            onEdit={openEdit}
-            onDelete={confirmDelete}
-            onToggleEnabled={(s, enabled) =>
-              updateMutation.mutate({ id: s.id, enabled })
-            }
-          />
+          <Group key={server.id} justify="space-between" wrap="nowrap">
+            <Stack gap={2} style={{ minWidth: 0 }}>
+              <Group gap="xs">
+                <Text fw={500} truncate>
+                  {server.name}
+                </Text>
+                <Badge size="xs" variant="light">
+                  {server.transport.toUpperCase()}
+                </Badge>
+              </Group>
+              <Text
+                size="xs"
+                c="dimmed"
+                truncate
+                style={{ fontFamily: "ui-monospace, Menlo, monospace" }}
+              >
+                {server.url}
+              </Text>
+            </Stack>
+
+            <Group gap="xs" wrap="nowrap">
+              <Switch
+                size="sm"
+                checked={server.enabled}
+                aria-label={t("Enabled")}
+                onChange={(event) =>
+                  updateMutation.mutate({
+                    id: server.id,
+                    enabled: event.currentTarget.checked,
+                  })
+                }
+              />
+              <ActionIcon
+                variant="subtle"
+                aria-label={t("Edit")}
+                onClick={() => openEdit(server)}
+              >
+                <IconPencil size={16} />
+              </ActionIcon>
+              <ActionIcon
+                variant="subtle"
+                color="red"
+                aria-label={t("Delete")}
+                onClick={() => confirmDelete(server)}
+              >
+                <IconTrash size={16} />
+              </ActionIcon>
+            </Group>
+          </Group>
         ))}
       </Stack>
 

apps/client/src/features/workspace/components/settings/components/ai-provider-settings.tsx

@@ -7,6 +7,7 @@ import {
   Button,
   Group,
   Modal,
+  NumberInput,
   Paper,
   PasswordInput,
   Select,
@@ -85,6 +86,9 @@ const formSchema = z.object({
   chatModel: z.string(),
   // Chat provider implementation (reasoning surfacing). Default openai-compatible.
   chatApiStyle: z.enum(["openai-compatible", "openai"]),
+  // Model context-window size (tokens) shown as the chat header badge's "max".
+  // Empty string = no limit (NumberInput emits "" when cleared).
+  chatContextWindow: z.union([z.number(), z.literal("")]),
   // Cheap model id for the anonymous public-share assistant; empty = use chatModel.
   publicShareChatModel: z.string(),
   // Agent-role id whose persona the public-share assistant adopts; empty =
@@ -312,6 +316,7 @@ export default function AiProviderSettings() {
     initialValues: {
       chatModel: "",
       chatApiStyle: "openai-compatible" as ChatApiStyle,
+      chatContextWindow: "" as number | "",
       publicShareChatModel: "",
       publicShareAssistantRoleId: "",
       embeddingModel: "",
@@ -335,6 +340,10 @@ export default function AiProviderSettings() {
     form.setValues({
       chatModel: settings.chatModel ?? "",
       chatApiStyle: settings.chatApiStyle ?? "openai-compatible",
+      // 0/unset = no limit → show an empty field (not a literal "0").
+      chatContextWindow: settings.chatContextWindow
+        ? settings.chatContextWindow
+        : "",
       publicShareChatModel: settings.publicShareChatModel ?? "",
       publicShareAssistantRoleId: settings.publicShareAssistantRoleId ?? "",
       embeddingModel: settings.embeddingModel ?? "",
@@ -365,6 +374,11 @@ export default function AiProviderSettings() {
       driver: "openai",
       chatModel: values.chatModel,
       chatApiStyle: values.chatApiStyle,
+      // Empty → 0, which clears the limit server-side (badge shows current only).
+      chatContextWindow:
+        typeof values.chatContextWindow === "number"
+          ? values.chatContextWindow
+          : 0,
       // Cheap model id for the anonymous public-share assistant; empty falls
       // back to chatModel server-side.
       publicShareChatModel: values.publicShareChatModel,
@@ -785,6 +799,22 @@ export default function AiProviderSettings() {
           {...form.getInputProps("chatApiStyle")}
         />
 
+        <NumberInput
+          mt="sm"
+          label={t("Context window (tokens)")}
+          description={t(
+            "Shows used / total in the chat header badge; empty hides the total.",
+          )}
+          placeholder={t("e.g. 200000")}
+          min={0}
+          step={1000}
+          allowDecimal={false}
+          allowNegative={false}
+          thousandSeparator=" "
+          disabled={isLoading}
+          {...form.getInputProps("chatContextWindow")}
+        />
+
         {/* Anonymous public-share assistant: a single master toggle + an
             optional cheaper model id. Reuses this card's driver/URL/key. */}
         <Group justify="space-between" align="center" wrap="nowrap" mt="md">

apps/client/src/features/workspace/services/ai-settings-service.ts

@@ -23,6 +23,9 @@ export interface IAiSettings {
   driver?: AiDriver;
   chatModel?: string;
   chatApiStyle?: ChatApiStyle;
+  // Chat model context-window size (tokens); shown as the "max" in the chat
+  // header context badge. 0/unset = no limit (badge shows the current size only).
+  chatContextWindow?: number;
   // Cheap model id for the anonymous public-share assistant; empty = chatModel.
   publicShareChatModel?: string;
   // Agent-role id whose persona the public-share assistant adopts; empty =
@@ -57,6 +60,8 @@ export interface IAiSettingsUpdate {
   driver?: AiDriver;
   chatModel?: string;
   chatApiStyle?: ChatApiStyle;
+  // Chat model context-window size (tokens); 0 clears the limit.
+  chatContextWindow?: number;
   publicShareChatModel?: string;
   // Agent-role id whose persona the public-share assistant adopts; empty =
   // built-in locked persona.

apps/server/src/core/ai-chat/ai-chat.service.spec.ts

@@ -292,6 +292,26 @@ describe('flushAssistant', () => {
     expect(f.metadata.contextTokens).toBe(15);
   });
 
+  it('completed: writes maxContextTokens when the model limit is > 0', () => {
+    const f = flushAssistant([toolStep], '', 'completed', {
+      contextTokens: 15,
+      maxContextTokens: 200_000,
+    });
+    expect(f.metadata.maxContextTokens).toBe(200_000);
+  });
+
+  it('omits maxContextTokens when the limit is unset or 0', () => {
+    const unset = flushAssistant([toolStep], '', 'completed', {
+      contextTokens: 15,
+    });
+    expect('maxContextTokens' in unset.metadata).toBe(false);
+    const zero = flushAssistant([toolStep], '', 'completed', {
+      contextTokens: 15,
+      maxContextTokens: 0,
+    });
+    expect('maxContextTokens' in zero.metadata).toBe(false);
+  });
+
   it('error: records the error and a derived finishReason', () => {
     const f = flushAssistant([], 'partial answer', 'error', { error: 'boom' });
     expect(f.status).toBe('error');

apps/server/src/core/ai-chat/ai-chat.service.ts

@@ -616,6 +616,9 @@ export class AiChatService implements OnModuleInit {
               contextTokens:
                 (usage?.inputTokens ?? 0) + (usage?.outputTokens ?? 0) ||
                 undefined,
+              // Admin-configured context-window size for this model (badge max).
+              // Resolved once per turn above; written to metadata only when > 0.
+              maxContextTokens: resolved?.chatContextWindow,
             }),
           );
           // Lifecycle: release the external MCP clients leased for this turn.
@@ -1223,6 +1226,10 @@ export function flushAssistant(
     finishReason?: string;
     usage?: ChatStreamUsage | StreamUsage | undefined;
     contextTokens?: number;
+    // Admin-configured context-window size (tokens) for this turn's model; the
+    // denominator of the client's "current / max" header badge. Written only
+    // when > 0 (0/unset = no limit known → the badge shows current only).
+    maxContextTokens?: number;
     error?: string;
   },
 ): AssistantFlush {
@@ -1253,6 +1260,9 @@ export function flushAssistant(
       normalizeStreamUsage(extra.usage as StreamUsage) ?? extra.usage;
   }
   if (extra?.contextTokens) metadata.contextTokens = extra.contextTokens;
+  if (extra?.maxContextTokens && extra.maxContextTokens > 0) {
+    metadata.maxContextTokens = extra.maxContextTokens;
+  }
   if (extra?.error) metadata.error = extra.error;
 
   return {

apps/server/src/database/repos/workspace/workspace.repo.ts

@@ -21,6 +21,7 @@ export const AI_PROVIDER_SETTINGS_ALLOWED: readonly string[] = [
   'driver',
   'chatModel',
   'chatApiStyle',
+  'chatContextWindow',
   'embeddingModel',
   'baseUrl',
   'embeddingBaseUrl',
@@ -255,11 +256,17 @@ export class WorkspaceRepo {
   ): Promise<Workspace> {
     const db = dbOrTx(this.db, trx);
     // Assemble the provider object IN SQL. Keys are fixed provider field names
-    // (sql.lit -> inlined literals, no injection); values are bound params cast
-    // to ::text — postgres.js sends bound params untyped, and jsonb_build_object's
-    // value args are polymorphic ("any"), so without the explicit ::text cast
-    // Postgres throws "could not determine data type of parameter $1". The result
-    // is a real jsonb object, never a double-encoded string. The CASE self-heals
+    // (sql.lit -> inlined literals, no injection); values are bound params with
+    // an explicit cast — postgres.js sends bound params untyped, and
+    // jsonb_build_object's value args are polymorphic ("any"), so without the
+    // cast Postgres throws "could not determine data type of parameter $1". The
+    // cast is branched by the JS runtime type so the value lands in jsonb with
+    // the matching JSON type: a number stays a JSON number (e.g.
+    // chatContextWindow → `{"chatContextWindow":200000}`, jsonb_typeof 'number'),
+    // a boolean a JSON boolean, everything else a JSON string. A plain `::text`
+    // for all would store a numeric field as the JSON STRING `"200000"`, which
+    // the client's `typeof === "number"` guards reject. The result is a real
+    // jsonb object, never a double-encoded string. The CASE self-heals
     // workspaces whose settings.ai.provider was previously corrupted into an
     // array/string.
     const entries = Object.entries(provider).filter(
@@ -267,7 +274,14 @@ export class WorkspaceRepo {
     );
     const patch = entries.length
       ? sql`jsonb_build_object(${sql.join(
-          entries.flatMap(([k, v]) => [sql.lit(k), sql`${v}::text`]),
+          entries.flatMap(([k, v]) => [
+            sql.lit(k),
+            typeof v === 'number'
+              ? sql`${v}::numeric`
+              : typeof v === 'boolean'
+                ? sql`${v}::boolean`
+                : sql`${v}::text`,
+          ]),
         )})`
       : sql`'{}'::jsonb`;
     return db

apps/server/src/integrations/ai/ai-provider-settings-keys.spec.ts

@@ -41,3 +41,35 @@ describe('UpdateAiSettingsDto.chatApiStyle', () => {
     expect(errs.find((e) => e.property === 'chatApiStyle')).toBeUndefined();
   });
 });
+
+/** DTO validation for chatContextWindow (@IsOptional @IsInt @Min(0)). */
+describe('UpdateAiSettingsDto.chatContextWindow', () => {
+  const errorsFor = async (chatContextWindow: unknown) =>
+    validate(plainToInstance(UpdateAiSettingsDto, { chatContextWindow }));
+
+  it('accepts a non-negative integer (incl. 0 = clear the limit)', async () => {
+    for (const v of [0, 200000]) {
+      const errs = await errorsFor(v);
+      expect(
+        errs.find((e) => e.property === 'chatContextWindow'),
+      ).toBeUndefined();
+    }
+  });
+
+  it('rejects a negative value', async () => {
+    const errs = await errorsFor(-1);
+    expect(errs.find((e) => e.property === 'chatContextWindow')).toBeDefined();
+  });
+
+  it('rejects a non-integer value', async () => {
+    const errs = await errorsFor(1.5);
+    expect(errs.find((e) => e.property === 'chatContextWindow')).toBeDefined();
+  });
+
+  it('accepts the field being omitted (optional)', async () => {
+    const errs = await validate(plainToInstance(UpdateAiSettingsDto, {}));
+    expect(
+      errs.find((e) => e.property === 'chatContextWindow'),
+    ).toBeUndefined();
+  });
+});

apps/server/src/integrations/ai/ai-settings.service.ts

@@ -27,6 +27,8 @@ export interface UpdateAiSettingsInput {
   driver?: AiDriver;
   chatModel?: string;
   chatApiStyle?: ChatApiStyle;
+  // Chat context-window size (tokens); 0/empty clears the limit.
+  chatContextWindow?: number;
   embeddingModel?: string;
   baseUrl?: string;
   embeddingBaseUrl?: string;
@@ -162,6 +164,8 @@ export class AiSettingsService {
       chatModel: provider.chatModel,
       // Plain passthrough; getChatModel defaults unset to 'openai-compatible'.
       chatApiStyle: provider.chatApiStyle,
+      // Admin-configured context-window size; 0/unset = no limit (badge denominator).
+      chatContextWindow: provider.chatContextWindow,
       // Cheap model id for the anonymous public-share assistant; reuses the chat
       // driver/baseUrl/apiKey. Empty/unset → callers fall back to chatModel.
       publicShareChatModel: provider.publicShareChatModel,
@@ -244,6 +248,7 @@ export class AiSettingsService {
       driver: provider.driver,
       chatModel: provider.chatModel,
       chatApiStyle: provider.chatApiStyle,
+      chatContextWindow: provider.chatContextWindow,
       embeddingModel: provider.embeddingModel,
       baseUrl: provider.baseUrl,
       embeddingBaseUrl: provider.embeddingBaseUrl,

apps/server/src/integrations/ai/ai.types.ts

@@ -35,6 +35,13 @@ export interface AiProviderSettings {
   // Chat provider implementation for the `openai` driver. Unset → defaults to
   // 'openai-compatible' (so reasoning is surfaced by default). See ChatApiStyle.
   chatApiStyle?: ChatApiStyle;
+  // Admin-configured chat model context-window size, in tokens. There is no
+  // provider-independent way to discover this (OpenAI's /v1/models usually omits
+  // it, Gemini/Ollama/OpenRouter each expose it differently), so it is entered
+  // manually. Surfaced to the chat client (via assistant message metadata) as the
+  // denominator of the header "current / max" context badge. Empty/0 = no limit
+  // known → the badge shows only the current context size.
+  chatContextWindow?: number;
   embeddingModel?: string;
   baseUrl?: string;
   // Embedding-specific base URL. Falls back to `baseUrl` when empty/unset.
@@ -73,6 +80,7 @@ export const PROVIDER_SETTINGS_KEYS = [
   'driver',
   'chatModel',
   'chatApiStyle',
+  'chatContextWindow',
   'embeddingModel',
   'baseUrl',
   'embeddingBaseUrl',
@@ -98,6 +106,10 @@ export const PROVIDER_SETTINGS_KEYS = [
 export interface ResolvedAiConfig extends Partial<AiProviderSettings> {
   driver?: AiDriver;
   chatModel?: string;
+  // Admin-configured chat context-window size (tokens); 0/unset = no limit. Used
+  // as the header context-badge denominator. Re-declared for parity with the
+  // explicit fields above.
+  chatContextWindow?: number;
   // Cheap model id for the public-share assistant; reuses the chat creds.
   publicShareChatModel?: string;
   // Agent-role id whose persona the public-share assistant adopts (empty/unset
@@ -117,6 +129,8 @@ export interface MaskedAiSettings {
   driver?: AiDriver;
   chatModel?: string;
   chatApiStyle?: ChatApiStyle;
+  // Admin-configured chat context-window size (tokens); 0/unset = no limit.
+  chatContextWindow?: number;
   embeddingModel?: string;
   baseUrl?: string;
   embeddingBaseUrl?: string;

apps/server/src/integrations/ai/dto/update-ai-settings.dto.ts

@@ -1,4 +1,4 @@
-import { IsIn, IsOptional, IsString } from 'class-validator';
+import { IsIn, IsInt, IsOptional, IsString, Min } from 'class-validator';
 import {
   AI_DRIVERS,
   AiDriver,
@@ -29,6 +29,13 @@ export class UpdateAiSettingsDto {
   @IsIn(CHAT_API_STYLES)
   chatApiStyle?: ChatApiStyle;
 
+  // Chat model context-window size in tokens (header context-badge denominator).
+  // 0 (or empty) clears the limit so the badge shows only the current context.
+  @IsOptional()
+  @IsInt()
+  @Min(0)
+  chatContextWindow?: number;
+
   @IsOptional()
   @IsString()
   embeddingModel?: string;

apps/server/test/integration/workspace-repo-ai-provider-settings.int-spec.ts

@@ -0,0 +1,91 @@
+import { Kysely, sql } from 'kysely';
+import { WorkspaceRepo } from '@docmost/db/repos/workspace/workspace.repo';
+import { getTestDb, destroyTestDb, createWorkspace } from './db';
+
+/**
+ * WorkspaceRepo.updateAiProviderSettings numeric round-trip (#189, #213).
+ *
+ * `chatContextWindow` is the first NUMERIC provider field routed through this
+ * generic SQL layer. The patch builder must cast a JS number so it lands in
+ * jsonb as a JSON NUMBER, not the JSON STRING `"200000"` — the client guards
+ * (`typeof === "number"`) reject a string, silently killing the `/ max` badge
+ * denominator. A plain `::text` cast (the prior code) regressed exactly this.
+ * These specs are real SQL and assert both the JS value type and the on-disk
+ * `jsonb_typeof`.
+ */
+describe('WorkspaceRepo.updateAiProviderSettings (numeric round-trip) [integration]', () => {
+  let db: Kysely<any>;
+  let repo: WorkspaceRepo;
+
+  beforeAll(() => {
+    db = getTestDb();
+    repo = new WorkspaceRepo(db as any);
+  });
+
+  afterAll(async () => {
+    await destroyTestDb();
+  });
+
+  it('stores chatContextWindow as a JSON number (not a "200000" string)', async () => {
+    const ws = await createWorkspace(db, { settings: undefined });
+
+    const updated = await repo.updateAiProviderSettings(ws.id, {
+      driver: 'openai',
+      chatModel: 'gpt-4o',
+      chatContextWindow: 200000,
+    });
+
+    // Returned row: the number survives as a real JS number, alongside the
+    // string fields which stay strings.
+    const provider = (updated.settings as any)?.ai?.provider;
+    expect(provider.chatContextWindow).toBe(200000);
+    expect(typeof provider.chatContextWindow).toBe('number');
+    expect(provider.driver).toBe('openai');
+    expect(provider.chatModel).toBe('gpt-4o');
+
+    // On disk: the jsonb value is typed 'number' (the must-fix assertion), and
+    // sibling string fields are typed 'string'.
+    const typed = await db
+      .selectFrom('workspaces')
+      .select([
+        sql<string>`jsonb_typeof(settings->'ai'->'provider'->'chatContextWindow')`.as(
+          'windowType',
+        ),
+        sql<string>`jsonb_typeof(settings->'ai'->'provider'->'chatModel')`.as(
+          'modelType',
+        ),
+      ])
+      .where('id', '=', ws.id)
+      .executeTakeFirstOrThrow();
+
+    expect(typed.windowType).toBe('number');
+    expect(typed.modelType).toBe('string');
+  });
+
+  it('re-reads chatContextWindow as a number after a partial-merge update', async () => {
+    const ws = await createWorkspace(db, {
+      settings: { ai: { provider: { driver: 'openai', chatModel: 'x' } } },
+    });
+
+    // Merge in only the numeric field; siblings must be preserved and the value
+    // must still be a JSON number, not a string.
+    await repo.updateAiProviderSettings(ws.id, { chatContextWindow: 128000 });
+
+    const row = await db
+      .selectFrom('workspaces')
+      .select([
+        'settings',
+        sql<string>`jsonb_typeof(settings->'ai'->'provider'->'chatContextWindow')`.as(
+          'windowType',
+        ),
+      ])
+      .where('id', '=', ws.id)
+      .executeTakeFirstOrThrow();
+
+    expect(row.windowType).toBe('number');
+    const provider = (row.settings as any)?.ai?.provider;
+    expect(provider.chatContextWindow).toBe(128000);
+    expect(provider.driver).toBe('openai');
+    expect(provider.chatModel).toBe('x');
+  });
+});