"A tool for inspecting and debugging Model Context Protocol (MCP) servers" matching MCP servers:

Local-first documentation for AI agents

A tool discovery MCP server that integrates with Azure DevOps wikis and code-graph-rag to match natural language goals to tools, enabling tool composition and proxy testing.

Provides verified, up-to-date model IDs, pricing, and specs for over 100 models across 19 providers, preventing AI agents from using outdated or hallucinated model names.

A Model Context Protocol (MCP) server that injects 'Just-in-Time' context into AI conversations based on file paths and glob patterns.

A Model Context Protocol (MCP) server designed to easily dump your codebase context into Large Language Models (LLMs).

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.

Automatically analyzes project dependencies to discover and download the most relevant documentation, enabling developers to quickly set up comprehensive project context.

Provides LLMs with secure, read-only access to local documentation by scanning directories, extracting content from PDF, DOCX, Markdown, and text files, and performing keyword searches.

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.

Automatically crawls documentation websites, converts them to organized markdown files, and generates condensed cheat sheets. Intelligently categorizes content into tools/APIs and provides local-first access to downloaded documentation.

Provides context about Toon Boom Harmony and its scripting API, enabling AI assistants to access Harmony's API documentation and help developers work with Harmony's scripting capabilities.

Enables engineers and AI assistants to search source-backed hardware design guidelines, retrieve detailed conditions and limitations, and trace citations to original sources, all through a read-only offline interface.

An MCP server that enables AI assistants to manage Context Repo prompts, documents, and collections with semantic search and progressive disclosure navigation.

Transforms any GitHub repository into a documentation hub for AI assistants, enabling up-to-date access to documentation and code to eliminate hallucinations.

A local-first MCP server that turns a .context/ folder of markdown files into a searchable knowledge layer for AI coding agents.

A Bun-based MCP server that allows AI models to query Swagger/OpenAPI documentation from local files or remote URLs. It enables users to search for APIs, retrieve detailed endpoint definitions, and fetch schemas to facilitate code generation and API integration.

Provides project-aware context for coding agents by selecting relevant AGENTS.md, docs, module paths, and decision records based on task, reducing redundant context loading via MCP stdio.

An MCP server that helps transfer C4 diagrams from DrawIO and PlantUML into a DocHub architecture repository.

MCP server that stores and queries shared company context, strategic spines, documents, and decision traces with citations and versioning.

This server provides an API to query Large Language Models using context from local files, supporting various models and file types for context-aware responses.