--- title: "mastra" type: "tool" slug: "mastra-ai-mastra" canonical_url: "https://www.graphcanon.com/tools/mastra-ai-mastra" github_url: "https://github.com/mastra-ai/mastra" homepage_url: "https://mastra.ai" stars: 25900 forks: 2372 primary_language: "TypeScript" license: "Other" categories: ["llm-frameworks", "ai-agents"] tags: ["agents", "llm", "ai", "evals", "javascript", "chatbots", "nextjs", "mcp"] updated_at: "2026-07-07T18:23:50.875975+00:00" --- # mastra > Mastra is a TypeScript framework for building AI-powered applications and agents. A modern TypeScript framework enabling the development of AI applications and agents. It supports model routing, autonomous agent building, workflow orchestration, human-in-the-loop interactions, context management, integrations with other frameworks/UIs, and more. ## Facts - Repository: https://github.com/mastra-ai/mastra - Homepage: https://mastra.ai - Stars: 25,900 · Forks: 2,372 · Open issues: 390 · Watchers: 95 - Primary language: TypeScript - License: Other - Last pushed: 2026-07-07T17:19:30+00:00 ## Categories - [LLM Frameworks](/categories/llm-frameworks.md) - [AI Agents](/categories/ai-agents.md) ## Tags agents, llm, ai, evals, javascript, chatbots, nextjs, mcp ## Related tools - [ECC](/tools/affaan-m-ecc.md) - The agent harness performance optimization system (★ 226,962) - [hermes-agent](/tools/nousresearch-hermes-agent.md) - The self-improving AI agent built by Nous Research (★ 210,880) - [AutoGPT](/tools/significant-gravitas-autogpt.md) - AutoGPT: Build, Deploy, and Run AI Agents (★ 185,417) - [ollama](/tools/ollama-ollama.md) - Get up and running with Kimi-K2.6, GLM-5.1, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and other models. (★ 175,659) - [prompts.chat](/tools/f-prompts-chat.md) - The world's largest open-source prompt library for AI (★ 165,019) - [transformers](/tools/huggingface-transformers.md) - 🤗 Transformers: the model-definition framework for state-of-the-art machine learning models (★ 162,347) - [langflow](/tools/langflow-ai-langflow.md) - Langflow is a powerful platform for building and deploying AI-powered agents and workflows. (★ 151,298) - [dify](/tools/langgenius-dify.md) - Production-ready platform for agentic workflow development (★ 148,070) ## README (excerpt) ```text # 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: - [**Model routing**](https://mastra.ai/models) - Connect to 40+ providers through one standard interface. Use models from OpenAI, Anthropic, Gemini, and more. - [**Agents**](https://mastra.ai/docs/agents/overview) - 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. - [**Workflows**](https://mastra.ai/docs/workflows/overview) - 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**](https://mastra.ai/docs/workflows/suspend-and-resume) - Suspend an agent or workflow and await user input or approval before resuming. Mastra uses [storage](https://mastra.ai/docs/server-db/storage) to remember execution state, so you can pause indefinitely and resume where you left off. - **Context management** - Give your agents the right context at the right time. Provide [conversation history](https://mastra.ai/docs/memory/conversation-history), [retrieve](https://mastra.ai/docs/rag/overview) data from your sources (APIs, databases, files), and add human-like memory with [Observational Memory](https://mastra.ai/docs/memory/observational-memory) so your agents behave coherently. - **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. - [**MCP servers**](https://mastra.ai/docs/tools-mcp/mcp-overview) - 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. - **Production essentials** - Shipping reliable agents takes ongoing insight, evaluation, and iteration. With built-in [evals](https://mastra.ai/docs/evals/overview) and [observability](https://mastra.ai/docs/observability/overview), 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: ```shell npm create mastra@latest ``` Follow the [Installation guide](https://mastra.ai/docs/getting-started/installation) for step-by-step setup with the CLI or a manual install. If you're new to AI agents, check out our [templates](https://mastra.ai/docs/getting-started/templates), [course](https://mastra.ai/course), and [YouTube videos](https://youtube.com/@mastra-ai) to start building with Mastra today.
Alternative: Use this pre-built prompt to get started ```md Make new Mastra project. Mastra = framework for AI apps + agents on modern TypeScript stack. Before run command, ask these questions one by one. Wait for answers unless already given: Project name? (default: "my-mastra-app") Provider? (default: "openai", options: "openai", "anthropic", "groq", "google", "cerebras", "mistral") Provider rules: Allowed provider -> use it. Any other value -> use "openai". Run with answers: npm create mastr ``` --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/tools/mastra-ai-mastra`](/api/graphcanon/tools/mastra-ai-mastra) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_