Tambo
tambo.co- Category
- AI Agents
- Rank
- No. 282Tools index
- Pricing
- Freemium
- Type
- TOOL
- Use case
- Agent Building
- Interfaces
- Web · MCP · API · SDK
- Builder
- @tambo-ai
- GitHub
- 11.2k stars
- Latest release
- web-v0.135.1
- Date
About
An open-source React toolkit that enables developers to add AI agents to their applications using existing components. It handles streaming, state management, and MCP while allowing agents to render your UI components with proper styling and logic.
What it does
Tambo turns natural-language requests into interactive application views. Developers describe approved components and their inputs with schemas; the agent selects among them, streams data into them, and can later revise persistent elements such as notes, carts, spreadsheets, or task boards.
Why it's ranked here
Tambo has a coherent end-to-end model: schema-defined components become agent tools, streamed output becomes visible UI, and stateful components remain editable across requests. It also covers operational gaps that often become separate projects, including conversation storage, reconnection, browser-side tools, authentication context, and hosted or self-managed execution.
What's good
The component boundary is explicit and constrained by schemas, so the model selects from application-owned UI instead of inventing arbitrary markup. Streaming includes cancellation, error recovery, and reconnection. Browser-side tools can access React state, authenticated requests, or the DOM. MCP support covers tools, prompts, elicitations, and sampling.
Tradeoffs
The main path assumes React and requires developers to describe every available component and tool with schemas. Applications also need a backend, either Tambo Cloud or the Docker-based self-hosted service. Each thread owner needs an identity key or access token. Provider breadth does not remove the work of securing local tools and defining safe inputs.
How to use it well
Use Tambo when a React product already has trusted components and needs an agent to choose, populate, and update them conversationally. Start with narrow schemas, register only safe actions, and pass page or user context deliberately. It does not replace your design system, authentication provider, or the product logic behind each tool.
Technical notes+
The root package.json defines an npm workspace monorepo spanning react-sdk, cli, create-tambo-app, packages/*, and apps/*, with Turbo build, lint, type-check, and test scripts. packages/client/src/index.ts exposes the framework-agnostic TamboClient, event streaming, tool execution, JSON Schema conversion, registries, and MCP APIs. packages/backend/src/index.ts exports createTamboBackend, storage operations, tool-source conversion, skill-provider operations, and custom events. packages/db/src/index.ts uses Drizzle with node-postgres and a shared pool capped at 75 connections. packages/react-ui-base/src/index.ts publishes unstyled compound primitives for messages, inputs, thread history, elicitation, reasoning, tool calls, prompts, and resources. packages/vite-config/src/index.ts builds preserved-module ESM and optional CJS output, generates declarations, preserves client directives, and emits source maps.
Observed
- License
- MIT unless otherwise noted; the API workspace is Apache-2.0.
- Primary language
- TypeScript and TSX.
- Packaging
- npm workspace monorepo with React SDK, framework-agnostic client, backend, CLI, app creator, UI primitives, and shared packages.
- Install surface
- Scaffold through npm create tambo-app; the React SDK is published under the @tambo-ai scope.
- Interfaces
- React library, framework-agnostic client library, CLI and scaffolder, backend API, and MCP client integration.
- Deployment
- Hosted backend through Tambo Cloud or self-hosted backend through Docker.
- Model providers
- Supports OpenAI, Anthropic, Cerebras, Google Gemini, Mistral, and OpenAI-compatible providers.
Read from README.md, package.json, packages/db/src/index.ts, packages/core/src/index.ts, packages/client/src/index.ts, packages/backend/src/index.ts, packages/testing/src/index.ts, packages/vite-config/src/index.ts, packages/react-ui-base/src/index.ts, packages/client/src/mcp/index.ts, packages/backend/src/model/index.ts, packages/client/src/schema/index.ts, packages/db/src/operations/index.ts, packages/react-ui-base/src/message/index.tsx, packages/react-ui-base/src/elicitation/index.tsx.
What it can do
Add AI agents to React applications
Existing React components and application code → React application with integrated AI agent functionality
Handle streaming data from AI agents
AI agent responses and data streams → Real-time updated UI components with streamed content
Manage state between AI agents and UI components
AI agent interactions and component state changes → Synchronized application state across agents and components
Process Model Control Protocol (MCP) communications
MCP messages and protocols → Processed AI model interactions and responses
Render existing UI components through AI agents
React components and AI agent instructions → Rendered UI components with preserved styling and logic
Integrate AI agent capabilities into existing component architecture
Current React component structure and AI agent requirements → Enhanced components with AI agent integration
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