📖 The AI Tool Bible

Mastra

✓ Editorially verified

Open-source TypeScript framework for building, deploying, and observing AI agents and workflows.

Freemium· Free open-source core (Apache 2.0); Enterprise license availableAgentsMulti-model (90+ providers)8.1 / 10

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Best for

Pick Mastra if you're a TypeScript team building agents or multi-step AI workflows and want typed primitives, observability, and MCP support out of the box.

Skip if

Skip it if your stack is Python-first or you need the mature plugin ecosystem of LangChain/LlamaIndex today.

Mastra is a TypeScript-first framework for building production AI agents, multi-step workflows, and copilots. It bundles typed agent primitives, a graph-based workflow engine, conversation and semantic memory, evals/traces/metrics for observability, and a model router that talks to 90+ LLM providers behind one interface. You scaffold a project with `npm create mastra` and ship to Vercel, Netlify, Cloudflare, or a plain Node server.

The pitch is aimed at TypeScript engineers who don't want to drop into Python LangChain/LangGraph land to build serious agentic systems. Core is Apache 2.0 and free to use with no seat or usage tiers; an Enterprise tier adds source-available extensions for larger orgs. Mastra also authors MCP (Model Context Protocol) servers, so its tools and data sources plug into Claude Desktop, Cursor, and any MCP-aware client.

It slots neatly into existing Next.js / React stacks rather than asking you to adopt a new runtime, and the built-in evals + tracing meaningfully reduce the "how do I know my agent is working" problem that plagues most home-grown agent stacks.

Editor's take

Mastra is the most credible TypeScript-native answer to LangGraph we've seen, and the bundled evals and tracing are a real differentiator over rolling your own agent loop. The Apache 2.0 core plus MCP-first posture make it a safe long-term bet for serious Next.js teams.

— The AI Tool Bible editorial team

Pros

✅ TypeScript-native, fits cleanly into Next.js/Node stacks
✅ Apache 2.0 core with no seat or usage limits
✅ Built-in evals, traces, and metrics for agent observability
✅ Model router across 90+ LLM providers
✅ First-class MCP server support

Cons

⚠️ TypeScript only; Python shops will look elsewhere
⚠️ Younger ecosystem than LangChain/LlamaIndex
⚠️ Enterprise features are source-available, not OSS

Use cases

ai-agentsworkflow-orchestrationragcopilotsmcp-serversagent-observability

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