Instant LLM Context for AI Agents and Developers

Context7 is a robust platform designed to create, manage, and leverage context libraries for Large Language Models (LLMs), AI agents, and developers. It automatically pulls high-quality, targeted code snippets from documentation repositories, delivering them as ready-to-use context for AI systems. Built by the Upstash team, you can enjoy Context7 with confidence knowing it’s backed by proven expertise.

Key Benefits:
✅ Precise Context: Extracts clean, relevant snippets from up-to-date documentation
✅ Focused Content: Includes only code and descriptions—no fluff or filler
✅ Free Tier: Up to 50 queries per day for personal use at no cost
✅ Broad Compatibility: Works seamlessly with MCP servers (e.g., Cursor, Windsurf)
✅ Fast Integration: Generate project-specific context in minutes and embed Context7 links directly into your documentation

Context7 transforms documentation into actionable context through a streamlined pipeline:

1. Document Parsing: Supports a variety of formats:

   • Markdown (.md, .mdx)
   • Plain Text (.txt)
   • ReStructuredText (.rst)
   • Jupyter Notebooks (.ipynb)

2. Context Extraction: Uses LLM models to pull code snippets and craft concise, descriptive metadata.

3. Embedding Generation: Converts snippets and metadata into vector embeddings for fast, accurate retrieval.

4. Contextual Retrieval: Delivers relevant code examples instantly via API or web interface.

1. Add your project to Context7 using one of the methods below.
2. Once processed, access your documentation as contextual snippets.
3. Refine results by searching topics and adjusting token size as needed.

Boost your docs with instant code examples by adding a Context7 link:

<a href="https://context7.com/YOUR_PROJECT/llm.txt?tokenLimit=MAX_TOKEN_LIMIT" target="_blank">
  See LLM.txt with code examples
</a>

This keeps users in your documentation while giving them quick access to implementation snippets.

Head to context7.com/add-package and add your project via our simple web interface.

1. Create a JSON file with your project details (see schema below).
2. Submit a Pull Request to our repository.
3. Once approved and merged, your project will be indexed and available.

{
  "settings": {
    "project": "project-name", // Unique, URL-friendly identifier
    "title": "Human-Readable Title", // Display name
    "docsRepoUrl": "https://github.com/organization/repo",
    "folders": ["docs"], // Optional: folders to include
    "excludeFolders": ["archive", "old"] // Optional: folders to exclude
  },
  "version": {
    "lastUpdate": "2023-03-25", // ISO 8601 timestamp
    "totalTokens": 0, // Set by system after processing
    "totalPages": 0, // Set by system after processing
    "totalSnippets": 0, // Set by system after processing
    "averageTokens": 0, // Set by system after processing
    "parseDuration": 0, // Set by system after processing
    "state": "initial", // Initial state for new projects
    "errorCount": 0 // Set by system after processing
  }
}

Coming soon!

We’d love your input! See our contribution guidelines to get started.

Help us improve by reporting bugs or suggesting features here.