TanStack AI is a TypeScript SDK for building applications that stream AI responses, call tools, run agents, produce structured output, and handle multimodal or realtime interactions. Developers use it across frameworks and AI providers through shared typed interfaces and provider adapters. The catalogue entries are add-ons for working with this SDK.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add TanStack/ai --skill servergit clone --depth 1 https://github.com/TanStack/aiWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/tanstack/ai/server)<a href="https://agentmods.dev/skills/tanstack/ai/server"><img src="https://agentmods.dev/badge/skills/tanstack/ai/server/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/tanstack/ai/server"><img src="https://agentmods.dev/badge/skills/tanstack/ai/server.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00083 | $0.02273 |
| Opus 5.5 | $0.00033 | $0.00909 |
| Sonnet 5.5 | $0.00017 | $0.00455 |
| Haiku 4.5 | $0.00008 | $0.00227 |
Grade A, and why
ai-persistence/server scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 29d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 234 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Server Chat Persistence
Builds on ai-persistence. Package:
@tanstack/ai-persistence.
withPersistence(persistence) is a ChatMiddleware that writes chat state
to a backend: messages, runs, interrupts (optional metadata). It does not
mutate the chunk stream and does not replace delivery durability.
Setup
import {
chat,
chatParamsFromRequest,
toServerSentEventsResponse,
} from '@tanstack/ai'
import { openaiText } from '@tanstack/ai-openai'
import { withPersistence } from '@tanstack/ai-persistence'
// Your adapter — see ai-persistence/stores.
import { persistence } from './persistence'
export async function POST(request: Request) {
const params = await chatParamsFromRequest(request)
const stream = chat({
adapter: openaiText('gpt-5.5'),
messages: params.messages,
threadId: params.threadId,
runId: params.runId,
...(params.resume ? { resume: params.resume } : {}),
middleware: [withPersistence(persistence)],
})
return toServerSentEventsResponse(stream)
}
Always pass threadId and runId from the client (via
chatParamsFromRequest / body helpers). Forward resume when the client
resolves pending interrupts.
For dev and tests, memoryPersistence() from @tanstack/ai-persistence is a
drop-in backend that implements all four stores in process.
What each store does
| Store | Role | Required? |
|---|---|---|
messages |
Full model-message transcript load/save | Yes for withPersistence |
runs |
Run status, timing, usage, errors | Optional; needed for interrupt durability |
interrupts |
Pending/resolved tool approvals & waits | Optional; requires runs |
metadata |
App-owned namespaced key/value | Optional |
Named shapes: ChatTranscriptPersistence (floor), ChatPersistence (all four).
Annotate your factory with one of these, not with bare AIPersistence —
the unparameterized type is the all-optional bag, and withPersistence rejects
it because stores.messages is possibly undefined.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 29d ago Changed · +11 lines c1f39cde49ed
- 1mo ago Changed · +5 lines f038f45cfac3
- 1mo ago First seen · 218 lines · 83 tokens per session scan A d5d16cebd380
ai-persistence/server is a skill published in the GitHub repository TanStack/ai (3,199 stars, last pushed today), licensed MIT. It adds 83 tokens to every session and 2,273 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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