"Information or context about 'context7'" matching MCP servers:

A Model Context Protocol server that fetches up-to-date, version-specific documentation and code examples from libraries directly into LLM prompts, helping developers get accurate answers without outdated or hallucinated information.

A drop-in Context7 MCP proxy that manages multiple API keys, balancing quota usage, caching responses, and providing failover for the standard Context7 tools. It lets MCP clients like OpenCode use the standard Context7 tools without worrying about account selection or quota limits.

Enables AI agents to query OpenRouter model information including prices, ELO rankings, context, and perform comparisons.

Provides LLMs with up-to-date, version-specific documentation and code examples directly from library sources, eliminating outdated training data and hallucinated APIs by fetching current documentation at prompt time.

Provides access to the Context7 API for searching up-to-date documentation, code examples, API references, and troubleshooting help across thousands of programming libraries and frameworks. Enables developers and AI agents to quickly find accurate documentation, compare libraries, get migration guides, and resolve coding issues.

Provides LLMs with up-to-date, version-specific documentation and code examples from library sources directly into prompts, eliminating outdated code generation and hallucinated APIs.

Enables AI assistants to access up-to-date library documentation through MCP tools for resolving library IDs and querying docs.

Provides real-time access to code library documentation and examples through Context7 API integration, enabling AI assistants to retrieve up-to-date technical documentation, code snippets, and best practices for various programming libraries.

Enables querying private documentation with tools for version resolution, stale reference checking, and receipt export.

Local-first documentation for AI agents

An MCP server that preserves LLM context by intercepting large data outputs and returning only concise summaries or relevant sections. It enables efficient sandboxed code execution, file processing, and documentation indexing across multiple programming languages and authenticated CLIs.

Deterministic dependency + CVE context for AI coding tools, over the Model Context Protocol. A ~0.85 MB pure-Rust MCP server.

Provides up-to-date, version-specific documentation and code examples for libraries and frameworks directly into AI prompts, eliminating outdated code generation and hallucinated APIs.

Provides AI assistants with real-time visibility into your codebase's internal libraries, team patterns, naming conventions, and usage frequencies to generate code that matches your team's actual practices.

MCP server providing deep PostgreSQL context to AI assistants, including schema DDL, index health, foreign key associations, query execution plans, and performance statistics via read-only tools.

Aggregator MCP proxy that collapses N downstream MCP servers into 4 meta-tools with progressive tool discovery, and compresses large tool outputs (HTML→Markdown, JSON summarization) with full-output retrieval via read_more and a per-session token-savings report.

Durable project-memory MCP: decisions, constraints, and pipelines across Claude sessions

Intelligent context manager for AI coding assistants that uses a three-level memory system (core, active, archive) to remember project context across conversations.

A high-performance MCP server providing up-to-date documentation for Go, npm, Python, Rust, Docker, Kubernetes, Terraform, and more — fetched from official sources, not training data.

Enables AI coding agents to consult a project's Git-versioned Markdown knowledge base over local stdio — checking knowledge health, listing the catalog, searching topics, and reading guides before acting. Access stays read-only, so project guidance, decisions, and lessons learned remain shared with human teammates and traceable beside the code.