OpenApps

Context7 MCP server — tools & history

Context7 MCP server: observed open status, tool schemas, linked apps and version history.

Context7

Endpoint: https://mcp.context7.com/mcp

Observed status: open. Checked: 2026-10-11T06:21:26+00:00.

Linked apps

  • Context7

    Up-to-date docs for LLMs and AI code editors

  • Context7

    Upstash Context7 MCP server for up-to-date documentation lookup. Pull version-specific documentation and code examples directly from source repositories into your LLM context.

Observed tools

  • query-docs — Retrieves and queries up-to-date documentation and code examples from Context7 for any programming library or framework. You must call 'Resolve Context7 Library ID' tool first to obtain the exact Context7-compatible library ID required to use this tool, UNLESS the user explicitly provides a library ID in the format '/org/project' or '/org/project/version' in their query. Do not call this tool more than 3 times per question. If you know the programming language the user is working in, pass it as `language` so the results match their setup.
  • resolve-library-id — Resolves a package/product name to a Context7-compatible library ID and returns matching libraries. You MUST call this function before 'Query Documentation' tool to obtain a valid Context7-compatible library ID UNLESS the user explicitly provides a library ID in the format '/org/project' or '/org/project/version' in their query. Each result includes: - Library ID: Context7-compatible identifier (format: /org/project) - Name: Library or package name - Description: Short summary - Code Snippets: Number of available code examples - Source Reputation: Authority indicator (High, Medium, Low, or Unknown) - Benchmark Score: Quality indicator (100 is the highest score) - Versions: List of versions if available. Use one of those versions if the user provides a version in their query. The format of the version is /org/project/version. For best results, select libraries based on name match, source reputation, snippet coverage, benchmark score, and relevance to your use case. Selection Process: 1. Analyze the query to understand what library/package the user is looking for 2. Return the most relevant match based on: - Name similarity to the query (exact matches prioritized) - Description relevance to the query's intent - Documentation coverage (prioritize libraries with higher Code Snippet counts) - Source reputation (consider libraries with High or Medium reputation more authoritative) - Benchmark Score: Quality indicator (100 is the highest score) Response Format: - Return the selected library ID in a clearly marked section - Provide a brief explanation for why this library was chosen - If multiple good matches exist, acknowledge this but proceed with the most relevant one - If no good matches exist, clearly state this and suggest query refinements For ambiguous queries, request clarification before proceeding with a best-guess match. IMPORTANT: Do not call this tool more than 3 times per question. If you cannot find what you need after 3 calls, use the best result you have.

Data as of 2026-10-11T06:21:26+00:00.

OpenApps records store listings and observed changes. Store ranks are not download counts; launch dates may be derived or use the first observation. Coverage gaps are shown in the interactive catalog.

REST API specification · Guide for AI clients · Manage API keys and MCP connections