Context7

Set up Context7 for your coding agents with a single command. Thectx7CLI requires Node.js 18 or newer.

Authenticates via OAuth, generates an API key, and installs the appropriate skill. You can choose between CLI + Skills or MCP mode. Use--cursor,--claude, or--opencodeto target a specific agent.

To remove the generated setup later, runnpx ctx7 remove. If you globally installed the CLI withnpm install -g ctx7, remove that package separately withnpm uninstall -g ctx7.

To configure manually, use the Context7 server URLhttps://mcp.context7.com/mcpwith your MCP client and pass your API key via theAuthorization: Bearer YOUR_API_KEYheader. See the link below for client-specific setup instructions.

If you already know exactly which library you want to use, add its Context7 ID to your prompt. That way, Context7 can skip the library-matching step and directly retrieve docs.

Implement basic authentication with Supabase. use library /supabase/supabase for API and docs.

The slash syntax tells Context7 exactly which library to load docs for.

To get documentation for a specific library version, just mention the version in your prompt:

How do I set up Next.js 14 middleware? use context7

Context7 will automatically match the appropriate version.

If you installed viactx7 setup, a skill is configured automatically that triggers Context7 for library-related questions. To set up a rule manually instead, add one to your coding agent:

- Cursor:Cursor Settings > Rules
- Claude Code:CLAUDE.md
- Or the equivalent in your coding agent

Always use Context7 when I need library/API documentation, code generation, setup or configuration steps without me having to explicitly ask.

- ctx7 library <name> <query>: Searches the Context7 index by library name and returns matching libraries with their IDs.
- ctx7 docs <libraryId> <query>: Retrieves documentation for a library using a Context7-compatible library ID (e.g.,/mongodb/docs,/vercel/next.js).

- resolve-library-id: Resolves a general library name into a Context7-compatible library ID.

- query(required): The user's question or task (used to rank results by relevance)
- libraryName(required): The name of the library to search for

- libraryId(required): Exact Context7-compatible library ID (e.g.,/mongodb/docs,/vercel/next.js)
- query(required): The question or task to get relevant documentation for

1- Context7 projects are community-contributed and while we strive to maintain high quality, we cannot guarantee the accuracy, completeness, or security of all library documentation. Projects listed in Context7 are developed and maintained by their respective owners, not by Context7. If you encounter any suspicious, inappropriate, or potentially harmful content, please use the "Report" button on the project page to notify us immediately. We take all reports seriously and will review flagged content promptly to maintain the integrity and safety of our platform. By using Context7, you acknowledge that you do so at your own discretion and risk.

2- This repository hosts the MCP server’s source code. The supporting components — API backend, parsing engine, and crawling engine — are private and not part of this repository.

This is a web browser that enables your coding agent, such as Claude Code, to visit websites on your behalf and assist you in identifying bugs or creating UI test cases.

MCP server that ingests project docs once and lets Claude search by meaning instead of reading everything — saving tokens on large codebases

Easily provide codebase context to Large Language Models (LLMs).

The DHTMLX MCP server provides real-time access to official docs and a smart RAG.

Local codebase context compiler for AI coding agents, turning TypeScript/Node workspaces into compact, verifiable context packs.

The only RAG API built for Apple Development. Give your AI instant access to 100,000+ pages of official docs, recipes, and evolution proposals.

Free local RAG for Claude Code - Save tokens & time with vector search. Indexes markdown docs and finds relevant info without reading entire files (40x fewer tokens, 15x faster).

One shared context layer for AI agents and humans — live API specs, DB schemas, and versioned contracts across repos so every agent and teammate works from the same source of truth.

Local stdio MCP server that lets AI coding agents read and maintain structured architecture, rules, and decisions directly from your repository.

Official Context7 MCP server that brings up-to-date, version-specific library documentation and code examples into AI coding prompts.