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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: 6 months ago
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The TypeScript AI agent framework. ⚡ Assistants, RAG, observability. Supports any LLM: GPT-4, Claude, Gemini, Llama.

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README 

          
# Mastra



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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/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)