https://github.com/mastra-ai/mastra
The TypeScript AI agent framework. ⚡ Assistants, RAG, observability. Supports any LLM: GPT-4, Claude, Gemini, Llama.
https://github.com/mastra-ai/mastra
agents ai chatbots evals javascript llm mcp nextjs nodejs reactjs tts typescript workflows
Last synced: 7 days ago
JSON representation
The TypeScript AI agent framework. ⚡ Assistants, RAG, observability. Supports any LLM: GPT-4, Claude, Gemini, Llama.
- Host: GitHub
- URL: https://github.com/mastra-ai/mastra
- Owner: mastra-ai
- License: other
- Created: 2024-08-06T20:44:31.000Z (8 months ago)
- Default Branch: main
- Last Pushed: 2025-04-07T22:22:13.000Z (7 days ago)
- Last Synced: 2025-04-07T22:22:28.316Z (7 days ago)
- Topics: agents, ai, chatbots, evals, javascript, llm, mcp, nextjs, nodejs, reactjs, tts, typescript, workflows
- Language: TypeScript
- Homepage: https://mastra.ai
- Size: 145 MB
- Stars: 11,736
- Watchers: 50
- Forks: 591
- Open Issues: 107
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
Awesome Lists containing this project
- Awesome-RAG - Mastra
- my-awesome-list - mastra - 4, Claude, Gemini, Llama. | mastra-ai | 11784 | (TypeScript)
- AiTreasureBox - mastra-ai/mastra - 04-07_11732_44](https://img.shields.io/github/stars/mastra-ai/mastra.svg)|the TypeScript AI agent framework| (Repos)
README
# Mastra 
Mastra is an opinionated TypeScript framework that helps you build AI applications and features quickly. It gives you the set of primitives you need: workflows, agents, RAG, integrations and evals. You can run Mastra on your local machine, or deploy to a serverless cloud.
The main Mastra features are:
| Features | Description |
| ------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| LLM Models | Mastra uses the [Vercel AI SDK](https://sdk.vercel.ai/docs/introduction) for model routing, providing a unified interface to interact with any LLM provider including OpenAI, Anthropic, and Google Gemini. You can choose the specific model and provider, and decide whether to stream the response. |
| [Agents](https://mastra.ai/docs/agents/overview) | Agents are systems where the language model chooses a sequence of actions. In Mastra, agents provide LLM models with tools, workflows, and synced data. Agents can call your own functions or APIs of third-party integrations and access knowledge bases you build. |
| [Tools](https://mastra.ai/docs/agents/adding-tools) | Tools are typed functions that can be executed by agents or workflows, with built-in integration access and parameter validation. Each tool has a schema that defines its inputs, an executor function that implements its logic, and access to configured integrations. |
| [Workflows](https://mastra.ai/docs/workflows/overview) | Workflows are durable graph-based state machines. They have loops, branching, wait for human input, embed other workflows, do error handling, retries, parsing and so on. They can be built in code or with a visual editor. Each step in a workflow has built-in OpenTelemetry tracing. |
| [RAG](https://mastra.ai/docs/rag/overview) | Retrieval-augemented generation (RAG) lets you construct a knowledge base for agents. RAG is an ETL pipeline with specific querying techniques, including chunking, embedding, and vector search. |
| [Integrations](https://mastra.ai/docs/local-dev/integrations) | In Mastra, integrations are auto-generated, type-safe API clients for third-party services that can be used as tools for agents or steps in workflows. |
| [Evals](https://mastra.ai/docs/08-running-evals) | Evals are automated tests that evaluate LLM outputs using model-graded, rule-based, and statistical methods. Each eval returns a normalized score between 0-1 that can be logged and compared. Evals can be customized with your own prompts and scoring functions. |
## Quick Start
### Prerequisites
- Node.js (v20.0+)
## Get an LLM provider API key
If you don't have an API key for an LLM provider, you can get one from the following services:
- [OpenAI](https://platform.openai.com/)
- [Anthropic](https://console.anthropic.com/settings/keys)
- [Google Gemini](https://ai.google.dev/gemini-api/docs)
- [Groq](https://console.groq.com/docs/overview)
- [Cerebras](https://inference-docs.cerebras.ai/introduction)
If you don't have an account with these providers, you can sign up and get an API key. Anthropic require a credit card to get an API key. Some OpenAI models and Gemini do not and have a generous free tier for its API.
## Create a new project
The easiest way to get started with Mastra is by using `create-mastra`. This CLI tool enables you to quickly start building a new Mastra application, with everything set up for you.
```bash
npx create-mastra@latest
```
### Run the script
Finally, run `mastra dev` to open the Mastra playground.
```bash copy
npm run dev
```
If you're using Anthropic, set the `ANTHROPIC_API_KEY`. If you're using Gemini, set the `GOOGLE_GENERATIVE_AI_API_KEY`.
## Contributing
Looking to contribute? All types of help are appreciated, from coding to testing and feature specification.
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](./DEVELOPMENT.md)
## Support
We have an [open community Discord](https://discord.gg/BTYqqHKUrf). 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](https://github.com/mastra-ai/mastra)