Context7 is a platform designed to provide large language models and AI code editors with up-to-date, version-specific code documentation and examples directly within their prompts. Built in TypeScript and maintained by Upstash, the project addresses a fundamental problem in AI-assisted coding: LLMs are trained on outdated information and often generate hallucinated APIs or code examples based on old package versions. Context7 solves this by fetching current documentation and code examples from source repositories and injecting them directly into the LLM's context, eliminating the need for developers to switch between tabs or deal with inaccurate information.
The platform operates in two distinct modes to accommodate different workflows. The CLI plus Skills mode installs a skill that guides agents to fetch documentation using ctx7 CLI commands without requiring Model Context Protocol support. The MCP mode registers Context7 as a native MCP server, allowing agents to call documentation tools natively. Both approaches are designed to be seamless integrations into existing coding workflows, with support for popular AI code editors including Cursor, Claude Code, and OpenCode. Installation is streamlined through a single command that handles OAuth authentication and API key generation.
Context7 provides several core tools for developers. The CLI includes commands like ctx7 library for searching the Context7 index by library name and ctx7 docs for retrieving documentation using Context7-compatible library IDs. The MCP tools include resolve-library-id for converting general library names into Context7 IDs and query-docs for fetching relevant documentation. Users can specify exact library versions in their prompts to receive version-specific documentation, and they can use library IDs with slash syntax to skip the library-matching step entirely.
The project is distributed across multiple npm packages including the MCP server, CLI tool, TypeScript SDK, Vercel AI SDK tools, and a pi.dev extension, providing flexibility for different integration scenarios. The repository itself hosts the MCP server's source code, while the API backend, parsing engine, and crawling engine remain private infrastructure.
According to GitGenius tracking data, Context7 has accumulated 58,579 stars and maintains active development with a median issue and pull request response latency of 10.1 hours across 2,156 tracked items. The most active issue labels are bug with 70 items, documentation with 67 items, and mcp with 53 items, reflecting the project's focus on reliability and MCP integration. The core development team includes enesgules with 2,975 tracked events, fahreddinozcan with 1,744 events, and enesakar with 601 events. The project shares contributors with related repositories including Anthropic's Claude Code, Airbyte, and claude-mem, indicating its integration within a broader ecosystem of AI development tools.
The platform has gained significant visibility through media coverage, with multiple YouTube creators highlighting its effectiveness for AI coding workflows. Context7 operates under an MIT license and maintains community engagement through social channels including X, Discord, and its official website at context7.com.
