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title: TanStack AI Enters the RC Phase | daily.dev
description: TanStack AI has moved into its release candidate phase ahead of a stable v1 release. The framework now supports 24 LLM providers, has adopted AG-UI as its...
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# TanStack AI Enters the RC Phase

**[TanStack](https://daily.dev/sources/tanstack-blog)** · 10 min read · 0 upvotes · 0 comments

## Summary

TanStack AI has moved into its release candidate phase ahead of a stable v1 release. The framework now supports 24 LLM providers, has adopted AG-UI as its official protocol, and offers a middleware system for chat persistence, agent harnesses, memory, and telemetry. Other highlighted capabilities include lazy tool calling, typed interrupts, unified media generation APIs (image, video, audio, transcription, TTS) across 100+ models, MCP support with type generation, agent sandboxing with ACP-compatible agents like Codex and Claude Code, and durable, resumable chat persistence requiring roughly 20 lines of code. The project is maintained by a three-person team and remains fully open source with no commercial roadmap.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://tanstack.com/blog/tanstack-ai-rc>

## Questions this post answers

### What is TanStack AI and what does it support now that it's entered release candidate?

TanStack AI is an open-source AI and agent framework built around a chat() method, now in release candidate status ahead of a stable v1. It supports 24 LLM providers, the AG-UI protocol used by 20+ agent frameworks, MCP with type-safe code generation, agent sandboxing with ACP-compatible agents like Codex and Claude Code, media generation across 100+ models, and persistent, resumable conversations.

_Developers evaluating AI application frameworks can track releases like this one on daily.dev._

### How does TanStack AI implement persistent and resumable chat conversations?

Persistence works by implementing a store that exposes conversation data, validating it against a conformance suite, then passing it into TanStack AI's persistence middleware. Durability adapters persist stream chunks in memory, Durable Streams, or other supported systems, so users can refresh mid-response or return after a month and resume exactly where they left off, in roughly 20 lines of code excluding the store implementation.

_Anyone building resumable AI chat experiences can follow framework updates like this via daily.dev._

### What is lazy tool calling in TanStack AI and why does it matter?

Lazy tool calling is a feature in TanStack AI that reduces token costs by controlling tool exposure through a simple boolean flag, rather than sending every tool definition upfront. It works alongside advanced interrupt scenarios, letting developers modify tool-call arguments or trigger multiple interrupts while keeping type safety intact end to end.

_Developers optimizing agent token costs can keep up with tooling patterns like this on daily.dev._

## Similar posts on daily.dev

- [TanStack Releases Framework Agnostic AI Toolkit](https://daily.dev/posts/tanstack-releases-framework-agnostic-ai-toolkit-j747yitl6) · InfoQ · 1 upvotes · 0 comments
- [TanStack Adds Framework-Agnostic AI Toolkit](https://daily.dev/posts/tanstack-adds-framework-agnostic-ai-toolkit-osqcmpmfc) · The New Stack · 18 upvotes · 0 comments

---

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