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Context7 MCP

Up-to-date, version-specific code documentation for AI coding assistants

Developer ToolsfreeClaudeCursorWindsurfGitHub CopilotVS CodeClaude Codeeasy✓ Verified
4.8
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How to Install Context7 MCP

$npx -y @upstash/context7-mcp@latest

Requires Claude Desktop, Cursor, Windsurf, or another MCP-compatible client.

About Context7 MCP

Context7 MCP delivers real-time, version-specific library documentation and code examples directly into your AI coding context. Built by Upstash, it eliminates outdated hallucinations in code generation by fetching fresh docs on demand — no local installation required as it runs over HTTP as a remote MCP server.

Context7 MCP is a Developer Tools MCP server designed for professional engineers and engineering teams. It enables wiring AI assistants into the inner loop of writing and shipping code by exposing Git, package, build, and CLI operations as MCP tools. Key capabilities include git and github operations (status, blame, prs), package and dependency inspection, build and test runner integration, and structured tool calls that work cleanly inside an LLM context. It integrates with Git, GitHub, GitLab, npm, pnpm, Docker, and common build systems, and is best suited for professional engineers and engineering teams who need reviewing diffs and opening prs from chat.

Key Features

  • documentation
  • developer-tools
  • code-generation
  • remote-mcp
  • Git and GitHub operations (status, blame, PRs)
  • Package and dependency inspection

Pricing

Free
$0
  • Core MCP server
  • Community support
  • Works with any MCP client
Pro
  • Everything in Free
  • Higher usage limits
  • Priority support
Business
Custom
  • Everything in Pro
  • SLA & SSO
  • Dedicated support

Tier details are indicative — visit the Context7 MCP website for current pricing.

Pros & Cons

Pros

  • Acts more like a pair programmer with real tools
  • Tight scoping (one repo, dry-run) limits blast radius
  • Keeps flow inside the editor

Cons

  • Write operations require explicit guardrails
  • Quality of output depends on repo hygiene
  • Larger monorepos may need extra filtering

Best For

  • Reviewing diffs and opening PRs from chat
  • Triaging CI failures
  • Scaffolding new packages or modules
  • Repo-wide refactors with verification

Screenshots

Screenshots coming soon —

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Our Take on Context7 MCP

Context7 is essential for any serious AI coding workflow — it eliminates outdated docs hallucinations by streaming fresh, version-pinned documentation directly into the model's context.

4.8

Frequently Asked Questions

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