# TanStack AI vs pi pi is built for an agent that runs in one process: a terminal coding agent, a bot, or a script. TanStack AI does that too, and it also lets you split the agent across a client and a server. Pick pi if you want pi's coding agent CLI or its subscription logins. Pick TanStack AI for everything else, and for any app with a browser in it. Both are open-source TypeScript toolkits under the MIT license. Both stream model output, call tools, run an agent loop, and talk to many providers. The difference is where the agent can run. ## Where the agent runs | | pi | TanStack AI | | --- | --- | --- | | In one process | Yes. `agentLoop()` runs next to the code that reads its events (`agent.subscribe`) | Yes. `chat()` returns an async stream you read in the same process. A harness keeps a session open across turns | | In a terminal | `pi-tui`, or `pi-coding-agent` | `runCli` from `@tanstack/ai-harness-cli`: line mode, print mode for scripts and CI, NDJSON, and ACP for editors | | Split across client and server | Not built in. `pi-protocol` and RPC mode can send events to another process. `streamProxy` keeps the loop in the browser and sends only the model call through your server | Built in. The loop and the server tools run on the server. The browser gets [AG-UI](https://docs.ag-ui.com/) events over HTTP and renders them with `useChat` | | With a browser UI | Your own code | `useChat` for React, Solid, Vue, Svelte, Preact, Angular and more, with approvals, reconnects and saved history | So pi gives you an agent to embed in one process. TanStack AI gives you the same agent, plus a client and a server that talk to each other when you need them. ## Pick TanStack AI when - **You build a terminal agent, a bot, or a script.** `chat()` runs the loop in your process. A [harness](../harness/overview) keeps the conversation open, queues and steers messages, and runs typed agents from code. See [Run a harness in the terminal](../harness/cli). - **You build a web app.** `useChat` renders the run on the client, and the run survives a slow network or a reload. See [UI](../ui/react) and [Resumable Streams](../resumable-streams/overview). - **Your tools must run on the server.** Database calls, secrets and paid APIs stay on the server. The browser never sees them. - **You want to define a tool once.** One schema gives the input and output types on the server and on the client. Add `.server()` or `.client()` to run it on either side. See [Tools](../tools/tools). - **You want people to approve tool calls.** `needsApproval` pauses the run, and the user answers in the terminal or in the browser. See [Tool approval](../tools/tool-approval). TanStack AI also has these, each in its own package: - **Coding-agent harnesses.** Run Claude Code, Codex, OpenCode, Grok Build, or any ACP agent as a chat backend, in a local process or a sandbox. The harness is experimental. See [Coding agents](../harness/coding-agents). - **Subagents.** A tool can run a child agent, and the client shows its run as a card. See [Subagents](../chat/subagents). - **Persistence.** Writes to your database, in your schema. See [Persistence](../persistence/overview). - **Media beyond chat.** Images, video, speech, transcription, music and realtime voice use the same adapters and persistence as chat. See [Generations](../media/generations). ## Pick pi when - **You want pi's coding agent as the product.** `pi-coding-agent` is a finished terminal agent that reads, edits and runs code in your repo. It saves sessions and loads extensions and skills. - **You sign in with a model subscription.** pi has OAuth logins for Claude Pro and Max, ChatGPT, GitHub Copilot and OpenRouter. - **The loop must stay in the browser.** `streamProxy` keeps the loop and the tools on the user's machine and sends only the model call through your server. ## How the core APIs map | pi | TanStack AI | | --------------------------------------------------------------------------------- | ------------------------------------------------------------------ | | `@earendil-works/pi-ai` | `@tanstack/ai` and one adapter package per provider | | `createModels()`, `setProvider(anthropicProvider())`, `models.getModel('anthropic', id)` | `anthropicText(id)` from `@tanstack/ai-anthropic` | | `models.streamSimple(model, context)` | `chat({ adapter, messages })` | | `models.completeSimple(model, context)` | `chat({ adapter, messages, stream: false })` | | `systemPrompt` in the context | `systemPrompts: ['...']` | | `AgentTool` with TypeBox `parameters` and `execute` | `toolDefinition({ inputSchema }).server(fn)` | | `agentLoop()` or the `Agent` class | `chat({ tools })`, which runs the loop | | `beforeToolCall` / `afterToolCall` | `middleware: [...]` with tool call hooks | | `agent.followUp(message)` | The [message queue](../chat/queueing) of `useChat` | | `agent.subscribe()` and `AgentEvent` | The AG-UI events of `chat()`, read by `useChat` on the client | | `streamProxy()` in the browser | `toServerSentEventsResponse` on the server, `useChat` on the client | | `@earendil-works/pi-mcp` | `@tanstack/ai-mcp`. See [MCP](../tools/mcp). | | `@earendil-works/pi-codemode` | `@tanstack/ai-code-mode`. See [Code Mode](../code-mode/code-mode). | ## Feature comparison Versions: pi `1.4` and TanStack AI 1.0. | Feature | pi | TanStack AI | | ---------------------- | ----------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------- | | License | MIT | MIT | | Main use | An agent in one process: coding agent CLI, and the libraries under it | Agents in one process, in a terminal, or split across client and server | | Wire protocol | In-process `AgentEvent` objects. Remote sessions over CBOR (`pi-protocol`) | Native AG-UI, in both directions | | Providers | About 35 in `pi-ai`, plus any OpenAI-compatible API | OpenAI, Anthropic, Gemini, Vertex, Bedrock, Grok, Groq, Mistral, OpenRouter, and more. Any OpenAI-compatible endpoint | | Subscription logins | OAuth for Claude Pro and Max, ChatGPT, GitHub Copilot, OpenRouter (Node only) | API keys | | UI | `pi-tui` for the terminal | Terminal (`runCli`), plus React, Solid, Vue, Svelte, Preact, Angular, Octane, Remix, React Native | | Tools | `AgentTool` with a TypeBox schema, run in the agent | One `toolDefinition()`, with `.server()` and `.client()` | | Tool approval | `beforeToolCall` can block a call | Per-tool `needsApproval`, with batched approvals and interrupts | | Steering and follow-up | Built-in queues on the `Agent` | A message queue in `useChat`. The harness also steers a running turn (experimental) | | Subagents | Task-owned child conversations in `pi-durable` (experimental) | Built in, with a card per child run | | Structured output | Constrained sampling for tool arguments | Typed message part, streamed with tools and kept in the history | | Token usage | Usage and cost on each assistant message | Usage on each model call, and cost when the provider reports it | | Persistence | JSONL session files with branching. `pi-durable` is experimental | `withPersistence` middleware, server or browser stores | | Resumable streams | `pi-durable` resumes a turn after a crash (experimental) | Built in. `useChat` reconnects by itself | | MCP client | `pi-mcp`: stdio and Streamable HTTP | `@tanstack/ai-mcp`: multi-server pools, generated types, lazy tools, managed lifecycle | | Code Mode | `pi-codemode`: QuickJS on Node, Bun and Cloudflare | 6 isolate drivers: Node, QuickJS WASM, QuickJS Bun, Cloudflare, Daytona, E2B | | Coding agents | `pi-coding-agent`, a CLI with extensions, skills and themes | Claude Code, Codex, OpenCode, Grok Build, and any ACP agent, on a local process or a sandbox | | Image | Image generation through OpenRouter | Stable, typed per model | | Video, speech, music | Not built in | Stable | | Realtime voice | Not built in | Stable: OpenAI, Gemini, Grok, ElevenLabs | To try TanStack AI, start with the [Quick Start](../getting-started/quick-start).