[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-tanstack-ai-corecustom-backend-integration":3,"mdc-t3o7hr-key":53,"related-org-tanstack-ai-corecustom-backend-integration":7988,"related-repo-tanstack-ai-corecustom-backend-integration":8132},{"slug":4,"name":5,"fn":6,"description":7,"org":8,"tags":12,"stars":24,"repoUrl":25,"updatedAt":26,"license":27,"forks":28,"topics":29,"repo":48,"sourceUrl":51,"mdContent":52},"ai-corecustom-backend-integration","ai-core\u002Fcustom-backend-integration","integrate custom backends with TanStack AI","Connect useChat to a non-TanStack-AI backend through custom connection adapters. ConnectConnectionAdapter (single async iterable) vs SubscribeConnectionAdapter (separate subscribe\u002Fsend). Customize fetchServerSentEvents() and fetchHttpStream() with auth headers, custom URLs, and request options. Import from framework package, not @tanstack\u002Fai-client.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},"tanstack","TanStack","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Ftanstack.png",[13,17,20,23],{"name":14,"slug":15,"type":16},"Backend","backend","tag",{"name":18,"slug":19,"type":16},"AI","ai",{"name":21,"slug":22,"type":16},"API Development","api-development",{"name":10,"slug":9,"type":16},2884,"https:\u002F\u002Fgithub.com\u002FTanStack\u002Fai","2026-07-17T06:06:39.855351",null,269,[19,30,31,32,33,34,35,36,37,38,39,40,41,42,43,9,44,45,46,47],"ai-agents","ai-sdk","anthropic","chatbot","function-calling","gemini","generative-ai","llm","multimodal","openai","react","solidjs","streaming","svelte","tool-calling","typescript","typescript-sdk","vue",{"repoUrl":25,"stars":24,"forks":28,"topics":49,"description":50},[19,30,31,32,33,34,35,36,37,38,39,40,41,42,43,9,44,45,46,47],"🤖 Type-safe, provider-agnostic TypeScript AI SDK for streaming chat, tool calling, agents, and multimodal apps across OpenAI, Anthropic, Gemini, React, Vue, Svelte, and Solid.","https:\u002F\u002Fgithub.com\u002FTanStack\u002Fai\u002Ftree\u002FHEAD\u002Fpackages\u002Fai\u002Fskills\u002Fai-core\u002Fcustom-backend-integration","---\nname: ai-core\u002Fcustom-backend-integration\ndescription: >\n Connect useChat to a non-TanStack-AI backend through custom connection\n adapters. ConnectConnectionAdapter (single async iterable) vs\n SubscribeConnectionAdapter (separate subscribe\u002Fsend). Customize\n fetchServerSentEvents() and fetchHttpStream() with auth headers,\n custom URLs, and request options. Import from framework package,\n not @tanstack\u002Fai-client.\ntype: composition\nlibrary: tanstack-ai\nlibrary_version: '0.10.0'\nsources:\n - 'TanStack\u002Fai:docs\u002Fchat\u002Fconnection-adapters.md'\n---\n\n# Custom Backend Integration\n\nThis skill builds on ai-core and ai-core\u002Fchat-experience. Read them first.\n\n## Setup\n\nConnect `useChat` to a custom SSE backend with auth headers:\n\n```typescript\nimport { useChat, fetchServerSentEvents } from '@tanstack\u002Fai-react'\n\nfunction Chat() {\n const { messages, sendMessage, isLoading } = useChat({\n connection: fetchServerSentEvents('https:\u002F\u002Fmy-api.com\u002Fchat', {\n headers: {\n Authorization: `Bearer ${token}`,\n },\n }),\n })\n\n return (\n \u003Cdiv>\n {messages.map((msg) => (\n \u003Cdiv key={msg.id}>\n \u003Cstrong>{msg.role}:\u003C\u002Fstrong>\n {msg.parts.map((part, i) => {\n if (part.type === 'text') {\n return \u003Cp key={i}>{part.content}\u003C\u002Fp>\n }\n return null\n })}\n \u003C\u002Fdiv>\n ))}\n \u003Cbutton onClick={() => sendMessage('Hello')}>Send\u003C\u002Fbutton>\n \u003C\u002Fdiv>\n )\n}\n```\n\nBoth `fetchServerSentEvents` and `fetchHttpStream` accept a static URL string\nor a function returning a string (evaluated per request), and a static options\nobject or a sync\u002Fasync function returning options (also evaluated per request).\nThis allows dynamic auth tokens and URLs without re-creating the adapter.\n\n## Core Patterns\n\n### 1. Custom SSE Backend with fetchServerSentEvents\n\nUse when your backend speaks SSE (`text\u002Fevent-stream`) with `data: {json}\\n\\n`\nframing. This is the recommended default.\n\n**Static options:**\n\n```typescript\nimport { useChat, fetchServerSentEvents } from '@tanstack\u002Fai-react'\n\nconst { messages, sendMessage } = useChat({\n connection: fetchServerSentEvents('https:\u002F\u002Fmy-api.com\u002Fchat', {\n headers: {\n Authorization: `Bearer ${token}`,\n 'X-Tenant-Id': tenantId,\n },\n credentials: 'include',\n }),\n})\n```\n\n**Dynamic URL and options (evaluated per request):**\n\n```typescript\nimport { useChat, fetchServerSentEvents } from '@tanstack\u002Fai-react'\n\nconst { messages, sendMessage } = useChat({\n connection: fetchServerSentEvents(\n () => `https:\u002F\u002Fmy-api.com\u002Fchat?session=${sessionId}`,\n async () => ({\n headers: {\n Authorization: `Bearer ${await getAccessToken()}`,\n },\n body: {\n provider: 'openai',\n model: 'gpt-4o',\n },\n }),\n ),\n})\n```\n\nThe `body` field in options is merged into the POST request body alongside\n`messages` and `data`, so the server receives `{ messages, data, provider, model }`.\n\n**Custom fetch client (for proxies, interceptors, retries):**\n\n```typescript\nimport { useChat, fetchServerSentEvents } from '@tanstack\u002Fai-react'\n\nconst { messages, sendMessage } = useChat({\n connection: fetchServerSentEvents('\u002Fapi\u002Fchat', {\n fetchClient: myCustomFetch,\n }),\n})\n```\n\n### 2. Custom NDJSON Backend with fetchHttpStream\n\nUse when your backend sends newline-delimited JSON (`application\u002Fx-ndjson`)\ninstead of SSE. Each line is one JSON-encoded `StreamChunk` followed by `\\n`.\n\n```typescript\nimport { useChat, fetchHttpStream } from '@tanstack\u002Fai-react'\n\nconst { messages, sendMessage } = useChat({\n connection: fetchHttpStream('https:\u002F\u002Fmy-api.com\u002Fchat', {\n headers: {\n Authorization: `Bearer ${token}`,\n },\n }),\n})\n```\n\n`fetchHttpStream` accepts the same URL and options signatures as\n`fetchServerSentEvents` (static or dynamic, sync or async). The only difference\nis the parsing: no `data:` prefix stripping, no `[DONE]` sentinel -- just one\nJSON object per line.\n\n**Dynamic options work identically:**\n\n```typescript\nimport { useChat, fetchHttpStream } from '@tanstack\u002Fai-react'\n\nconst { messages, sendMessage } = useChat({\n connection: fetchHttpStream(\n () => `\u002Fapi\u002Fchat?region=${region}`,\n async () => ({\n headers: { Authorization: `Bearer ${await refreshToken()}` },\n }),\n ),\n})\n```\n\n### 3. Fully Custom Connection Adapter\n\nFor protocols that don't fit SSE or NDJSON (WebSockets, gRPC-web, custom binary,\nserver functions), implement the `ConnectionAdapter` interface directly.\n\nThere are two mutually exclusive modes:\n\n**ConnectConnectionAdapter (pull-based \u002F async iterable):**\n\nUse when the client initiates a request and consumes the response as a stream.\nThis is the simpler model and covers most HTTP-based protocols.\n\n```typescript\nimport { useChat } from '@tanstack\u002Fai-react'\nimport type { ConnectionAdapter } from '@tanstack\u002Fai-react'\nimport type { StreamChunk, UIMessage } from '@tanstack\u002Fai'\n\nconst websocketAdapter: ConnectionAdapter = {\n async *connect(\n messages: Array\u003CUIMessage>,\n data?: Record\u003Cstring, any>,\n abortSignal?: AbortSignal,\n ): AsyncGenerator\u003CStreamChunk> {\n const ws = new WebSocket('wss:\u002F\u002Fmy-api.com\u002Fchat')\n\n \u002F\u002F Wait for connection\n await new Promise\u003Cvoid>((resolve, reject) => {\n ws.onopen = () => resolve()\n ws.onerror = (e) => reject(e)\n })\n\n \u002F\u002F Send messages\n ws.send(JSON.stringify({ messages, ...data }))\n\n \u002F\u002F Create an async queue to bridge WebSocket events to an async iterable\n const queue: Array\u003CStreamChunk> = []\n let resolve: (() => void) | null = null\n let done = false\n\n ws.onmessage = (event) => {\n const chunk: StreamChunk = JSON.parse(event.data)\n queue.push(chunk)\n resolve?.()\n }\n\n ws.onclose = () => {\n done = true\n resolve?.()\n }\n\n ws.onerror = () => {\n done = true\n resolve?.()\n }\n\n abortSignal?.addEventListener('abort', () => {\n ws.close()\n })\n\n \u002F\u002F Yield chunks as they arrive\n while (!done || queue.length > 0) {\n if (queue.length > 0) {\n yield queue.shift()!\n } else {\n await new Promise\u003Cvoid>((r) => {\n resolve = r\n })\n }\n }\n },\n}\n\nfunction Chat() {\n const { messages, sendMessage } = useChat({\n connection: websocketAdapter,\n })\n\n \u002F\u002F ... render messages\n}\n```\n\n**SubscribeConnectionAdapter (push-based \u002F separate subscribe + send):**\n\nUse for push-based protocols where the server can send data at any time\n(persistent WebSocket connections, MQTT, server push). The `subscribe` method\nreturns an `AsyncIterable\u003CStreamChunk>` that stays open, and `send` dispatches\nmessages through it.\n\n```typescript\nimport type { StreamChunk, UIMessage } from '@tanstack\u002Fai'\n\n\u002F\u002F SubscribeConnectionAdapter is exported from @tanstack\u002Fai-client\n\u002F\u002F (not re-exported by framework packages -- use ConnectionAdapter\n\u002F\u002F union type from @tanstack\u002Fai-react for typing)\nconst pushAdapter = {\n subscribe(abortSignal?: AbortSignal): AsyncIterable\u003CStreamChunk> {\n \u002F\u002F Return a long-lived async iterable that yields chunks\n \u002F\u002F whenever the server pushes them\n return createPersistentStream(abortSignal)\n },\n\n async send(\n messages: Array\u003CUIMessage>,\n data?: Record\u003Cstring, any>,\n abortSignal?: AbortSignal,\n ): Promise\u003Cvoid> {\n \u002F\u002F Dispatch messages; chunks arrive through subscribe()\n await persistentConnection.send(JSON.stringify({ messages, ...data }))\n },\n}\n\nfunction Chat() {\n const { messages, sendMessage } = useChat({\n connection: pushAdapter,\n })\n\n \u002F\u002F ... render messages\n}\n```\n\nThe `stream()` helper function (re-exported from `@tanstack\u002Fai-react`) provides\na shorthand for creating a `ConnectConnectionAdapter` from an async generator:\n\n```typescript\nimport { useChat, stream } from '@tanstack\u002Fai-react'\nimport type { StreamChunk, UIMessage } from '@tanstack\u002Fai'\n\nconst directAdapter = stream(async function* (\n messages: Array\u003CUIMessage>,\n data?: Record\u003Cstring, any>,\n): AsyncGenerator\u003CStreamChunk> {\n const response = await fetch('https:\u002F\u002Fmy-api.com\u002Fchat', {\n method: 'POST',\n headers: { 'Content-Type': 'application\u002Fjson' },\n body: JSON.stringify({ messages, ...data }),\n })\n\n const reader = response.body!.getReader()\n const decoder = new TextDecoder()\n let buffer = ''\n\n while (true) {\n const { done, value } = await reader.read()\n if (done) break\n\n buffer += decoder.decode(value, { stream: true })\n const lines = buffer.split('\\n')\n buffer = lines.pop() || ''\n\n for (const line of lines) {\n if (line.trim()) {\n yield JSON.parse(line) as StreamChunk\n }\n }\n }\n})\n\nconst { messages, sendMessage } = useChat({\n connection: directAdapter,\n})\n```\n\n## Common Mistakes\n\n### a. HIGH: Providing both connect and subscribe+send in connection adapter\n\nThe `ConnectionAdapter` interface has two mutually exclusive modes. Providing\nboth throws at runtime.\n\n```typescript\n\u002F\u002F WRONG -- throws \"Connection adapter must provide either connect or both\n\u002F\u002F subscribe and send, not both modes\"\nconst adapter = {\n async *connect(messages) {\n \u002F* ... *\u002F\n },\n subscribe(signal) {\n \u002F* ... *\u002F\n },\n async send(messages) {\n \u002F* ... *\u002F\n },\n}\n\n\u002F\u002F CORRECT -- pick one mode\n\u002F\u002F Option A: ConnectConnectionAdapter (pull-based)\nconst pullAdapter = {\n async *connect(messages, data, abortSignal) {\n \u002F\u002F ... yield StreamChunks\n },\n}\n\n\u002F\u002F Option B: SubscribeConnectionAdapter (push-based)\nconst pushAdapter = {\n subscribe(abortSignal) {\n return longLivedAsyncIterable\n },\n async send(messages, data, abortSignal) {\n await connection.dispatch({ messages, ...data })\n },\n}\n```\n\nSource: `ai-client\u002Fsrc\u002Fconnection-adapters.ts` line 116\n\n### b. MEDIUM: SSE browser connection limits\n\nBrowsers limit SSE connections to 6-8 per domain (the HTTP\u002F1.1 connection\nlimit). Multiple chat sessions on the same page, or multiple tabs to the\nsame origin, can exhaust this limit. New connections queue indefinitely until\nan existing one closes.\n\nMitigations:\n\n- Use HTTP\u002F2 (multiplexes streams over a single TCP connection; no per-domain limit)\n- Use `fetchHttpStream` instead of `fetchServerSentEvents` (each request is a\n standard POST, not a long-lived EventSource)\n- Close idle connections when not actively streaming\n- Use a single persistent WebSocket via `SubscribeConnectionAdapter` instead of\n per-request SSE connections\n\nSource: `docs\u002Fchat\u002Fconnection-adapters.md`\n\n### c. MEDIUM: HTTP stream without implementing reconnection\n\nSSE has built-in browser auto-reconnection via the `EventSource` API. HTTP\nstream (NDJSON via `fetchHttpStream`) does not -- if the connection drops\nmid-stream, the partial response is silently lost with no automatic retry.\n\nIf your application needs resilience to transient network errors with HTTP\nstreaming, implement retry logic in your connection adapter:\n\n```typescript\nimport { useChat } from '@tanstack\u002Fai-react'\nimport type { ConnectionAdapter } from '@tanstack\u002Fai-react'\nimport type { StreamChunk, UIMessage } from '@tanstack\u002Fai'\n\nconst resilientAdapter: ConnectionAdapter = {\n async *connect(\n messages: Array\u003CUIMessage>,\n data?: Record\u003Cstring, any>,\n abortSignal?: AbortSignal,\n ): AsyncGenerator\u003CStreamChunk> {\n const maxRetries = 3\n let attempt = 0\n\n while (attempt \u003C maxRetries) {\n try {\n const response = await fetch('https:\u002F\u002Fmy-api.com\u002Fchat', {\n method: 'POST',\n headers: { 'Content-Type': 'application\u002Fjson' },\n body: JSON.stringify({ messages, ...data }),\n signal: abortSignal,\n })\n\n if (!response.ok) {\n throw new Error(`HTTP ${response.status}`)\n }\n\n const reader = response.body!.getReader()\n const decoder = new TextDecoder()\n let buffer = ''\n\n while (true) {\n const { done, value } = await reader.read()\n if (done) break\n\n buffer += decoder.decode(value, { stream: true })\n const lines = buffer.split('\\n')\n buffer = lines.pop() || ''\n\n for (const line of lines) {\n if (line.trim()) {\n yield JSON.parse(line) as StreamChunk\n }\n }\n }\n\n return \u002F\u002F Stream completed successfully\n } catch (err) {\n if (abortSignal?.aborted) throw err\n attempt++\n if (attempt >= maxRetries) throw err\n \u002F\u002F Exponential backoff\n await new Promise((r) => setTimeout(r, 1000 * 2 ** attempt))\n }\n }\n },\n}\n\nconst { messages, sendMessage } = useChat({\n connection: resilientAdapter,\n})\n```\n\nNote: `fetchServerSentEvents` in TanStack AI uses `fetch()` under the hood (not\nthe browser `EventSource` API), so it also does not auto-reconnect. The SSE\nauto-reconnection advantage only applies when using the native `EventSource` API\ndirectly.\n\nSource: `docs\u002Fprotocol\u002Fhttp-stream-protocol.md`\n\n## Cross-References\n\n- See also: **ai-core\u002Fag-ui-protocol\u002FSKILL.md** -- Understanding the AG-UI protocol helps build compatible custom servers\n- See also: **ai-core\u002Fchat-experience\u002FSKILL.md** -- Full chat setup patterns including server-side `chat()` and `toServerSentEventsResponse()`\n- See also: **ai-core\u002Fmiddleware\u002FSKILL.md** -- Use middleware for analytics and lifecycle events on the server side\n",{"data":54,"body":60},{"name":5,"description":7,"type":55,"library":56,"library_version":57,"sources":58},"composition","tanstack-ai","0.10.0",[59],"TanStack\u002Fai:docs\u002Fchat\u002Fconnection-adapters.md",{"type":61,"children":62},"root",[63,72,78,85,99,933,954,960,967,988,996,1283,1291,1661,1695,1703,1890,1896,1924,2147,2180,2188,2462,2468,2481,2486,2494,2499,4095,4103,4131,4677,4704,5743,5749,5755,5766,6241,6254,6260,6265,6270,6317,6327,6333,6353,6358,7882,7916,7926,7932,7982],{"type":64,"tag":65,"props":66,"children":68},"element","h1",{"id":67},"custom-backend-integration",[69],{"type":70,"value":71},"text","Custom Backend Integration",{"type":64,"tag":73,"props":74,"children":75},"p",{},[76],{"type":70,"value":77},"This skill builds on ai-core and ai-core\u002Fchat-experience. 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The SSE\nauto-reconnection advantage only applies when using the native ",{"type":64,"tag":91,"props":7910,"children":7912},{"className":7911},[],[7913],{"type":70,"value":6343},{"type":70,"value":7915}," API\ndirectly.",{"type":64,"tag":73,"props":7917,"children":7918},{},[7919,7920],{"type":70,"value":6245},{"type":64,"tag":91,"props":7921,"children":7923},{"className":7922},[],[7924],{"type":70,"value":7925},"docs\u002Fprotocol\u002Fhttp-stream-protocol.md",{"type":64,"tag":79,"props":7927,"children":7929},{"id":7928},"cross-references",[7930],{"type":70,"value":7931},"Cross-References",{"type":64,"tag":6271,"props":7933,"children":7934},{},[7935,7947,7971],{"type":64,"tag":6275,"props":7936,"children":7937},{},[7938,7940,7945],{"type":70,"value":7939},"See also: ",{"type":64,"tag":552,"props":7941,"children":7942},{},[7943],{"type":70,"value":7944},"ai-core\u002Fag-ui-protocol\u002FSKILL.md",{"type":70,"value":7946}," -- Understanding the AG-UI protocol helps build compatible custom servers",{"type":64,"tag":6275,"props":7948,"children":7949},{},[7950,7951,7956,7958,7964,7965],{"type":70,"value":7939},{"type":64,"tag":552,"props":7952,"children":7953},{},[7954],{"type":70,"value":7955},"ai-core\u002Fchat-experience\u002FSKILL.md",{"type":70,"value":7957}," -- Full chat setup patterns including server-side ",{"type":64,"tag":91,"props":7959,"children":7961},{"className":7960},[],[7962],{"type":70,"value":7963},"chat()",{"type":70,"value":945},{"type":64,"tag":91,"props":7966,"children":7968},{"className":7967},[],[7969],{"type":70,"value":7970},"toServerSentEventsResponse()",{"type":64,"tag":6275,"props":7972,"children":7973},{},[7974,7975,7980],{"type":70,"value":7939},{"type":64,"tag":552,"props":7976,"children":7977},{},[7978],{"type":70,"value":7979},"ai-core\u002Fmiddleware\u002FSKILL.md",{"type":70,"value":7981}," -- Use middleware for analytics and lifecycle events on the server side",{"type":64,"tag":7983,"props":7984,"children":7985},"style",{},[7986],{"type":70,"value":7987},"html .light .shiki span {color: var(--shiki-light);background: var(--shiki-light-bg);font-style: var(--shiki-light-font-style);font-weight: var(--shiki-light-font-weight);text-decoration: var(--shiki-light-text-decoration);}html.light .shiki span {color: var(--shiki-light);background: var(--shiki-light-bg);font-style: var(--shiki-light-font-style);font-weight: var(--shiki-light-font-weight);text-decoration: var(--shiki-light-text-decoration);}html .default .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}html.dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}",{"items":7989,"total":8131},[7990,8006,8018,8030,8045,8057,8067,8077,8090,8100,8111,8121],{"slug":7991,"name":7991,"fn":7992,"description":7993,"org":7994,"tags":7995,"stars":8003,"repoUrl":8004,"updatedAt":8005},"aggregation","perform data aggregation in TanStack Table","Aggregate TanStack Table columns independently of grouping, including grand totals, caller-selected row totals, multiple keyed aggregations, custom context-based definitions, grouped merges, manual values, and worker constraints.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[7996,7999,8002],{"name":7997,"slug":7998,"type":16},"Data Analysis","data-analysis",{"name":8000,"slug":8001,"type":16},"Frontend","frontend",{"name":10,"slug":9,"type":16},28175,"https:\u002F\u002Fgithub.com\u002FTanStack\u002Ftable","2026-07-30T05:25:59.429787",{"slug":8007,"name":8007,"fn":8008,"description":8009,"org":8010,"tags":8011,"stars":8003,"repoUrl":8004,"updatedAt":8017},"api-not-found","diagnose TanStack Table API errors","Diagnose missing TanStack Table v9 exports, options, state slices, and instance methods. Load before inventing an API when code sees a type error, undefined feature method, absent object key, adapter mismatch, or v8-shaped example.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[8012,8015,8016],{"name":8013,"slug":8014,"type":16},"Debugging","debugging",{"name":8000,"slug":8001,"type":16},{"name":10,"slug":9,"type":16},"2026-07-30T05:26:05.418735",{"slug":8019,"name":8019,"fn":8020,"description":8021,"org":8022,"tags":8023,"stars":8003,"repoUrl":8004,"updatedAt":8029},"cell-selection","select rectangular cell ranges in tables","Select rectangular cell ranges with cellSelectionFeature: two-corner range state keyed by row and column id, mousedown\u002Fmouseenter handlers, selection edges, render-order resolution under pinning, and autoResetCellSelection. Load when ranges widen unexpectedly after sorting or column reordering, when a drag re-renders the whole table, or when building copy-to-clipboard from a selection.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[8024,8025,8026],{"name":7997,"slug":7998,"type":16},{"name":10,"slug":9,"type":16},{"name":8027,"slug":8028,"type":16},"UI Components","ui-components","2026-07-30T05:25:38.403427",{"slug":8031,"name":8031,"fn":8032,"description":8033,"org":8034,"tags":8035,"stars":8003,"repoUrl":8004,"updatedAt":8044},"client-vs-server","manage TanStack Table data pipelines","Choose client or server ownership for filtering, grouping, sorting, expanding, and pagination in TanStack Table v9. Load for manual* flags, mixed pipelines, server counts, or deciding which dataset each row-model stage receives.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[8036,8039,8040,8043],{"name":8037,"slug":8038,"type":16},"Data Pipeline","data-pipeline",{"name":8000,"slug":8001,"type":16},{"name":8041,"slug":8042,"type":16},"Performance","performance",{"name":10,"slug":9,"type":16},"2026-07-30T05:25:45.400104",{"slug":8046,"name":8046,"fn":8047,"description":8048,"org":8049,"tags":8050,"stars":8003,"repoUrl":8004,"updatedAt":8056},"column-faceting","build faceted filter UIs","Build faceted filter UIs with columnFacetingFeature, facetedRowModel, facetedUniqueValues, and facetedMinMaxValues. Load for facet counts, numeric ranges, own-filter exclusion, or server-page facet completeness.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[8051,8054,8055],{"name":8052,"slug":8053,"type":16},"Data Visualization","data-visualization",{"name":8000,"slug":8001,"type":16},{"name":10,"slug":9,"type":16},"2026-07-30T05:25:41.397257",{"slug":8058,"name":8058,"fn":8059,"description":8060,"org":8061,"tags":8062,"stars":8003,"repoUrl":8004,"updatedAt":8066},"column-filtering","implement column filtering in TanStack Table","Filter columns with columnFilteringFeature, filteredRowModel, filterFns, filterMeta, nested-row direction, and manualFiltering. Load for accessor compatibility, controlled filter updaters, fuzzy metadata, or client\u002Fserver ownership.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[8063,8064,8065],{"name":7997,"slug":7998,"type":16},{"name":8000,"slug":8001,"type":16},{"name":10,"slug":9,"type":16},"2026-07-30T05:25:53.391632",{"slug":8068,"name":8068,"fn":8069,"description":8070,"org":8071,"tags":8072,"stars":8003,"repoUrl":8004,"updatedAt":8076},"column-ordering","manage TanStack Table column ordering","Control TanStack Table v9 leaf columnOrder with stable IDs while accounting for pinning regions, visibility, and groupedColumnMode precedence. Load for drag-and-drop columns or rendered order that differs from state.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[8073,8074,8075],{"name":8000,"slug":8001,"type":16},{"name":10,"slug":9,"type":16},{"name":8027,"slug":8028,"type":16},"2026-07-30T05:26:03.37801",{"slug":8078,"name":8078,"fn":8079,"description":8080,"org":8081,"tags":8082,"stars":8003,"repoUrl":8004,"updatedAt":8089},"column-pinning","configure column pinning in TanStack Table","Pin columns into logical start, center, and end regions with columnPinningFeature and renderer-owned sticky CSS. Load for RTL offsets, z-index, backgrounds, overflow, widths, gaps, or overlaps.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[8083,8086,8087,8088],{"name":8084,"slug":8085,"type":16},"CSS","css",{"name":8000,"slug":8001,"type":16},{"name":10,"slug":9,"type":16},{"name":8027,"slug":8028,"type":16},"2026-07-30T05:25:55.377366",{"slug":8091,"name":8091,"fn":8092,"description":8093,"org":8094,"tags":8095,"stars":8003,"repoUrl":8004,"updatedAt":8099},"column-resizing","implement column resizing in TanStack Table","Wire columnResizingFeature, header.getResizeHandler, resize mode and direction, pointer or touch events, and performant CSS-variable updates. Load when resize state changes but widths do not, or large tables resize slowly.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[8096,8097,8098],{"name":8000,"slug":8001,"type":16},{"name":10,"slug":9,"type":16},{"name":8027,"slug":8028,"type":16},"2026-07-30T05:25:51.400011",{"slug":8101,"name":8101,"fn":8102,"description":8103,"org":8104,"tags":8105,"stars":8003,"repoUrl":8004,"updatedAt":8110},"column-sizing","configure column sizing in TanStack Table","Use columnSizingFeature numeric size, minSize, maxSize, getSize, getStart, getAfter, and total-size APIs in table, grid, or flex CSS. Load for auto or percentage misconceptions and sizing\u002Fpinning layout mismatch.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[8106,8107,8108,8109],{"name":8084,"slug":8085,"type":16},{"name":8000,"slug":8001,"type":16},{"name":10,"slug":9,"type":16},{"name":8027,"slug":8028,"type":16},"2026-07-30T05:25:48.703799",{"slug":8112,"name":8112,"fn":8113,"description":8114,"org":8115,"tags":8116,"stars":8003,"repoUrl":8004,"updatedAt":8120},"column-visibility","manage column visibility in TanStack Table","Hide columns with columnVisibilityFeature while rendering visibility-aware header, column, and cell collections. Load when hidden columns remain in the DOM, false-versus-absent state is confused, or enableHiding is misunderstood.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[8117,8118,8119],{"name":8000,"slug":8001,"type":16},{"name":10,"slug":9,"type":16},{"name":8027,"slug":8028,"type":16},"2026-07-30T05:25:47.367943",{"slug":8122,"name":8122,"fn":8123,"description":8124,"org":8125,"tags":8126,"stars":8003,"repoUrl":8004,"updatedAt":8130},"core","build data grids with TanStack Table","Use TanStack Table v9 as a headless data-grid state and row-processing engine. Load for first-table architecture, stable data and columns, row numbering with getDisplayIndex, semantic rendering, framework adapter choice, or deciding what Table owns versus the renderer.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[8127,8128,8129],{"name":7997,"slug":7998,"type":16},{"name":8000,"slug":8001,"type":16},{"name":8027,"slug":8028,"type":16},"2026-07-30T05:25:52.366295",125,{"items":8133,"total":918},[8134,8152,8166,8181,8192,8204,8218],{"slug":8135,"name":8135,"fn":8136,"description":8137,"org":8138,"tags":8139,"stars":24,"repoUrl":25,"updatedAt":8151},"ai-code-mode","execute sandboxed TypeScript code with LLMs","LLM-generated TypeScript execution in sandboxed environments: createCodeModeTool() with isolate drivers (createNodeIsolateDriver, createQuickJSIsolateDriver, createCloudflareIsolateDriver), codeModeWithSkills() for persistent skill libraries, trust strategies, skill storage (FileSystem, LocalStorage, InMemory, Mongo), client-side execution progress via code_mode:* custom events in useChat.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[8140,8142,8145,8148,8149],{"name":8141,"slug":31,"type":16},"AI SDK",{"name":8143,"slug":8144,"type":16},"Code Execution","code-execution",{"name":8146,"slug":8147,"type":16},"Sandboxing","sandboxing",{"name":10,"slug":9,"type":16},{"name":8150,"slug":45,"type":16},"TypeScript","2026-07-16T06:04:13.597905",{"slug":8153,"name":8153,"fn":8154,"description":8155,"org":8156,"tags":8157,"stars":24,"repoUrl":25,"updatedAt":8165},"ai-core","configure TanStack AI agent features","Entry point for TanStack AI skills. Routes to chat-experience, tool-calling, media-generation, structured-outputs, adapter-configuration, ag-ui-protocol, middleware, locks, custom-backend-integration, and debug-logging, plus the skills shipped by companion packages (@tanstack\u002Fai-persistence, @tanstack\u002Fai-code-mode). Use chat() not streamText(), openaiText() not createOpenAI(), toServerSentEventsResponse() not manual SSE, middleware hooks not onEnd callbacks.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[8158,8161,8162],{"name":8159,"slug":8160,"type":16},"Agents","agents",{"name":18,"slug":19,"type":16},{"name":8163,"slug":8164,"type":16},"Middleware","middleware","2026-07-30T05:26:10.404565",{"slug":8167,"name":8168,"fn":8169,"description":8170,"org":8171,"tags":8172,"stars":24,"repoUrl":25,"updatedAt":8180},"ai-coreadapter-configuration","ai-core\u002Fadapter-configuration","configure AI provider adapters","Provider adapter selection and configuration: openaiText, anthropicText, geminiText, ollamaText, grokText, groqText, openRouterText, bedrockText, openaiCompatible. Per-model type safety with modelOptions, reasoning\u002Fthinking configuration, runtime adapter switching, extendAdapter() for custom models, createModel(). Generic OpenAI-compatible providers (DeepSeek, Together, Fireworks, etc.) via openaiCompatible({ baseURL, apiKey, models }) from @tanstack\u002Fai-openai\u002Fcompatible. API key env vars: OPENAI_API_KEY, ANTHROPIC_API_KEY, GOOGLE_API_KEY\u002FGEMINI_API_KEY, XAI_API_KEY, GROQ_API_KEY, OPENROUTER_API_KEY, OLLAMA_HOST, BEDROCK_API_KEY (or AWS_BEARER_TOKEN_BEDROCK).\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[8173,8174,8177,8179],{"name":8141,"slug":31,"type":16},{"name":8175,"slug":8176,"type":16},"Configuration","configuration",{"name":8178,"slug":37,"type":16},"LLM",{"name":10,"slug":9,"type":16},"2026-07-16T06:04:17.82075",{"slug":8182,"name":8183,"fn":8184,"description":8185,"org":8186,"tags":8187,"stars":24,"repoUrl":25,"updatedAt":8191},"ai-coreag-ui-protocol","ai-core\u002Fag-ui-protocol","implement TanStack AI streaming protocol","Server-side AG-UI streaming protocol implementation: StreamChunk event types (RUN_STARTED, TEXT_MESSAGE_START\u002FCONTENT\u002FEND, TOOL_CALL_START\u002FARGS\u002FEND, RUN_FINISHED, RUN_ERROR, STEP_STARTED\u002FSTEP_FINISHED, STATE_SNAPSHOT\u002FDELTA, CUSTOM), toServerSentEventsStream() for SSE format, toHttpStream() for NDJSON format. For backends serving AG-UI events without client packages.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[8188,8189,8190],{"name":21,"slug":22,"type":16},{"name":8178,"slug":37,"type":16},{"name":10,"slug":9,"type":16},"2026-07-16T06:04:10.093367",{"slug":8193,"name":8194,"fn":8195,"description":8196,"org":8197,"tags":8198,"stars":24,"repoUrl":25,"updatedAt":8203},"ai-corechat-experience","ai-core\u002Fchat-experience","implement chat experiences with TanStack AI","End-to-end chat implementation: server endpoint with chat() and toServerSentEventsResponse(), client-side useChat hook with fetchServerSentEvents(), message rendering with UIMessage parts, multimodal content, thinking\u002Freasoning display. Covers streaming states, connection adapters, and message format conversions. NOT Vercel AI SDK — uses chat() not streamText().\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[8199,8200,8201,8202],{"name":21,"slug":22,"type":16},{"name":8000,"slug":8001,"type":16},{"name":8178,"slug":37,"type":16},{"name":10,"slug":9,"type":16},"2026-07-30T05:26:11.505241",{"slug":8205,"name":8206,"fn":8207,"description":8208,"org":8209,"tags":8210,"stars":24,"repoUrl":25,"updatedAt":8217},"ai-coreclient-persistence","ai-core\u002Fclient-persistence","implement browser chat persistence for TanStack AI","Browser chat persistence on useChat \u002F ChatClient: localStoragePersistence, sessionStoragePersistence, indexedDBPersistence. Client-authoritative (adapter, full transcript) vs server-authoritative (persistence: true, no client cache). Reload restore, pending interrupts, mid-stream rejoin with delivery durability. Use for SPA reload durability — NOT server history alone. No extra package: the adapters ship in the framework packages.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[8211,8212,8213,8216],{"name":18,"slug":19,"type":16},{"name":8000,"slug":8001,"type":16},{"name":8214,"slug":8215,"type":16},"Persistence","persistence",{"name":10,"slug":9,"type":16},"2026-07-30T05:53:35.503176",{"slug":4,"name":5,"fn":6,"description":7,"org":8219,"tags":8220,"stars":24,"repoUrl":25,"updatedAt":26},{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[8221,8222,8223,8224],{"name":18,"slug":19,"type":16},{"name":21,"slug":22,"type":16},{"name":14,"slug":15,"type":16},{"name":10,"slug":9,"type":16}]