Mastra Docs▌

by mastra-ai
Mastra Docs: AI assistants with direct access to Mastra.ai’s full knowledge base for faster, smarter support and insight
Provides AI assistants with direct access to Mastra.ai's complete knowledge base.
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / Developers building with Mastra framework
- / Learning Mastra's AI agent capabilities
- / Troubleshooting integration issues
capabilities
- / Query Mastra framework documentation
- / Search API references and guides
- / Access code examples and tutorials
- / Retrieve configuration details
- / Find integration instructions
what it does
Gives AI assistants direct access to Mastra.ai's complete documentation and knowledge base for answering questions about the TypeScript AI framework.
about
Mastra Docs is an official MCP server published by mastra-ai that provides AI assistants with tools and capabilities via the Model Context Protocol. Mastra Docs: AI assistants with direct access to Mastra.ai’s full knowledge base for faster, smarter support and insight It is categorized under productivity, developer tools.
how to install
You can install Mastra Docs in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
license
NOASSERTION
Mastra Docs is released under the NOASSERTION license.
readme
Mastra
Mastra is a framework for building AI-powered applications and agents with a modern TypeScript stack.
It includes everything you need to go from early prototypes to production-ready applications. Mastra integrates with frontend and backend frameworks like React, Next.js, and Node, or you can deploy it anywhere as a standalone server. It's the easiest way to build, tune, and scale reliable AI products.
Why Mastra?
Purpose-built for TypeScript and designed around established AI patterns, Mastra gives you everything you need to build great AI applications out-of-the-box.
Some highlights include:
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Model routing - Connect to 40+ providers through one standard interface. Use models from OpenAI, Anthropic, Gemini, and more.
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Agents - Build autonomous agents that use LLMs and tools to solve open-ended tasks. Agents reason about goals, decide which tools to use, and iterate internally until the model emits a final answer or an optional stopping condition is met.
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Workflows - When you need explicit control over execution, use Mastra's graph-based workflow engine to orchestrate complex multi-step processes. Mastra workflows use an intuitive syntax for control flow (
.then(),.branch(),.parallel()). -
Human-in-the-loop - Suspend an agent or workflow and await user input or approval before resuming. Mastra uses storage to remember execution state, so you can pause indefinitely and resume where you left off.
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Context management - Give your agents the right context at the right time. Provide conversation history, retrieve data from your sources (APIs, databases, files), and add human-like working and semantic memory so your agents behave coherently.
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Integrations - Bundle agents and workflows into existing React, Next.js, or Node.js apps, or ship them as standalone endpoints. When building UIs, integrate with agentic libraries like Vercel's AI SDK UI and CopilotKit to bring your AI assistant to life on the web.
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MCP servers - Author Model Context Protocol servers, exposing agents, tools, and other structured resources via the MCP interface. These can then be accessed by any system or agent that supports the protocol.
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Production essentials - Shipping reliable agents takes ongoing insight, evaluation, and iteration. With built-in evals and observability, Mastra gives you the tools to observe, measure, and refine continuously.
Get started
The recommended way to get started with Mastra is by running the command below:
npm create mastra@latest
Follow the Installation guide for step-by-step setup with the CLI or a manual install.
If you're new to AI agents, check out our templates, course, and YouTube videos to start building with Mastra today.
Documentation
Visit our official documentation.
Build with AI
Learn how to make your agent a Mastra expert by following the Build with AI guide.
Contributing
Looking to contribute? All types of help are appreciated, from coding to testing and feature specification. Read CONTRIBUTING.md for more details on how to get involved.
If you are a developer and would like to contribute with code, please open an issue to discuss before opening a Pull Request.
Information about the project setup can be found in the development documentation
Support
We have an open community Discord. Come and say hello and let us know if you have any questions or need any help getting things running.
It's also super helpful if you leave the project a star here at the top of the page
Licensing
This repository uses a dual-license model:
- Apache License 2.0 — The core framework and the vast majority of this codebase is open source under Apache-2.0.
- Mastra Enterprise License — Code in any directory named
ee/(e.g.,packages/core/src/auth/ee/) is source-available under the Mastra Enterprise License. These features require a valid enterprise license for production use but can be freely used for development and testing.
See LICENSE.md for the full license mapping and ee/LICENSE for the enterprise license terms.
Security
We are committed to maintaining the security of this repo and of Mastra as a whole. If you discover a security finding we ask you to please responsibly disclose this to us at security@mastra.ai and we will get back to you.
FAQ
- What is the Mastra Docs MCP server?
- Mastra Docs is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for Mastra Docs?
- This profile displays 47 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.8 out of 5—verify behavior in your own environment before production use.
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.8★★★★★47 reviews- ★★★★★Daniel Agarwal· Dec 28, 2024
Mastra Docs is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Tariq Haddad· Dec 24, 2024
Mastra Docs has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★Dhruvi Jain· Dec 4, 2024
Useful MCP listing: Mastra Docs is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Amina Zhang· Dec 4, 2024
According to our notes, Mastra Docs benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Oshnikdeep· Nov 23, 2024
According to our notes, Mastra Docs benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Zara Gonzalez· Nov 19, 2024
Useful MCP listing: Mastra Docs is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Omar Sethi· Nov 19, 2024
We evaluated Mastra Docs against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Ganesh Mohane· Oct 14, 2024
I recommend Mastra Docs for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Tariq Ghosh· Oct 10, 2024
Strong directory entry: Mastra Docs surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Soo Mensah· Oct 10, 2024
We wired Mastra Docs into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
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