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TanStack AI vs. Vercel AI SDK: a tool-sharing vs. split-implementation choice for React

A LogRocket comparison breaks down how TanStack AI and the Vercel AI SDK handle tools, typing, and runtime support in React apps.

LogRocket published a TanStack AI vs. Vercel AI SDK comparison on January 16, authored by Ikeh Akinyemi, focused on picking an AI library for React teams shipping tool-using assistants.

Key takeaways from LogRocket’s comparison:

  • Tooling model: TanStack AI defines tools once with toolDefinition() and binds them to .server() or .client() while preserving types; Vercel AI SDK typically defines tools on the server with tool() and exposes them in the client via useChat, keeping server execution and client UI as separate pieces.
  • Maturity (Dec 2025): TanStack AI is described as alpha; Vercel AI SDK is described as stable (v6) and includes Agents plus Tool Execution Approval.
  • Provider support: TanStack AI lists adapters for OpenAI, Anthropic, Gemini, and Ollama; Vercel AI SDK is positioned as supporting OpenAI, Anthropic, Google, and 20+ providers.
  • Modality coverage: TanStack AI is credited with broader coverage (text, images, video, audio, TTS, transcription, structured outputs) versus Vercel AI SDK’s focus on text, structured outputs, and embeddings.
  • Ecosystem/MCP: Vercel AI SDK is noted as having MCP support available, while TanStack AI’s MCP support is described as a roadmap item.