"A system for retrieving medical knowledge, especially in medical imaging, and generating reports" matching MCP servers:

A Model Context Protocol (MCP) server for Canvas Medical API/SDK development assistance, providing streamlined access to Canvas Medical documentation and AI-powered development tools.

Provides structured instructions to Cursor for generating comprehensive system summaries of Node.js/TypeScript codebases.

An MCP server that guides AI assistants to navigate documentation using their built-in tools (grep, file reading) instead of traditional RAG.

Provides a read-only MCP interface to the Santismm Knowledge Platform, offering tools to retrieve curated content on engineering, AI patterns, architectures, governance, and agent taxonomy with structured output in English, Spanish, and Portuguese.

A Model Context Protocol server that exposes an airline design system as a queryable knowledge base, enabling AI to discover components, find components for use cases, and scaffold prototypes.

Enables AI agents and MCP clients to search, retrieve, and read documents across unified knowledge sources including ShowDoc, GitHub, Gitee, ZenTao, Evernote, and Tencent Docs. It also supports connecting external MCP servers as additional knowledge sources.

Enables LLMs to search and retrieve information from large technical documentation (OpenAPI specs, markdown) via intelligent chunking and semantic search.

Serves markdown knowledge from a git repository over MCP, providing tools to list, search, and retrieve documents.

Enables searching and reading AWS knowledge from sources the official AWS Knowledge MCP Server does not index, including re:Post community Q&A, kiro.dev documentation, and AWS Builder Center posts.

Provides coding agents with a shared, Markdown-based engineering knowledge base to search, capture, create, and update internal conventions, API details, infrastructure configs, and development setup via lightweight MCP tools.

Enables coding agents to query a team knowledge base via MCP, performing semantic search and asking questions that return grounded, citation-backed answers from ingested documents.

Enables AI assistants to search, retrieve, and browse Markdown documentation in a local folder, then answer questions with cited sources.

Provides content agents with structured search over editorial guidelines, visual templates, and past post outcomes, enabling auditable proposals that cite rule IDs.

Recon Fuzz Knowledge MCP

Enables evidence-based retrieval across official BMC Helix product documentation and isolated private project knowledge, with product, version, project, source, and section provenance. Supports version-aware multi-product indexing, hybrid lexical and optional semantic search, and read-only access to local evidence without touching live Helix systems.

MCP server for searching and citing ASTGL (As The Geek Learns) articles about MCP servers, local AI, and AI automation. Provides semantic search, direct Q\&A, and topic browsing across 20 authoritative articles with pre-computed embeddings.

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.

Enables natural-language Q&A over multi-source documents (PDF/Markdown/web) with a self-reflective retrieval-augmented agent that cites sources, retries on poor retrieval or grounding, and supports multi-turn memory.

A local document processing server that can index various document formats (PDF, DOCX, TXT, HTML) and answer questions based on their content using the Model Context Protocol.

A high-performance MCP server that aggregates Wikipedia, arXiv, Context7, and DevDocs into a unified interface for AI agents.