"How to document a codebase using Markdown" matching MCP servers:

MCP server that indexes Markdown, Word, HTML, and PDF documents into a SQLite knowledge graph with CJK+Latin full-text search and cross-document reference tracking. Runs drift audits to surface stale policies, conflicting research claims, superseded ADRs, and undocumented code exports.

An MCP server that lets AI publish markdown documents to a clean, themed web UI. One tool call creates a shareable doc.

LLM Optimizer is an AI visibility intelligence platform. It analyzes how large language models and AI search engines perceive, cite, and recommend brands; then provides research-backed optimization strategies to improve that visibility.

An MCP server for codebase context that gives AI coding agents structural understanding through symbol graph, semantic search, blast radius, and convention detection tools.

Enables AI assistants to structurally understand a Moodle installation and its plugins, so they can answer codebase questions and scaffold plugins that follow existing conventions. It scans Moodle sources and generates Markdown context files, indexes, and MCP tools/resources/prompts for querying, diagnosing, and maintaining that understanding.

Enables permission-aware codebase onboarding inside IBM Bob by exposing only the code, history, and answers a user's role is allowed to see. It filters context before the model sees it, cites every item, and reports what was withheld.

Records how any command-line tool behaves (flags, stdin, outputs, exit codes, edge cases) as golden tests, then diffs a Rust or Go rewrite against the original to prove it behaves the same.

The Multi DB MCP Server is a high-performance implementation of the Database Model Context Protocol designed to revolutionize how AI agents interact with databases. Currently supporting MySQL and PostgreSQL databases.

A memory, docs, and repo context layer for engineering agents, providing typed persistent memory, RAG document retrieval, and repository-aware tools to recall decisions, runbooks, and operational knowledge across sessions.

Converts URL content to Markdown, providing two tools: one for extracting main article content and one for converting the entire HTML.

Turns a codebase into a queryable graph with semantic search, call graphs, and control/data flow analysis, served to AI coding agents via the Model Context Protocol.

A web scraping CLI tool that converts web pages to markdown and also runs as an MCP server for agent integration.

Enables AI agents to communicate with business agents across company boundaries using Google's A2A protocol, with tools for discovery, messaging, and connection management.

A lightweight MCP server that fetches URLs and returns clean, readable markdown, enabling AI assistants to read any webpage with article extraction, caching, and security features.

A local-first MCP server that indexes Markdown/Obsidian folders and lets AI clients retrieve cited local context through MCP.

Enables AI agents to create, manage, and track tasks within plans using Valkey as the persistence layer. Supports plan and task management with Markdown notes, status tracking, and prioritization through multiple transport protocols (SSE, Streamable HTTP, STDIO).

MCP server for driving Office add-ins (Excel, Word, Outlook, PowerPoint, OneNote) through high-level workflow tools and queries, enabling LLM agents to automate document tasks across Microsoft Office applications via a single Go binary.

Transforms a codebase into a queryable knowledge base for code understanding, impact analysis, ownership lookup, and more via CLI, HTTP API, or MCP.

A file management system powered by Claude AI that provides document access and manipulation through MCP protocol and Telegram bot integration, enabling users to interact with files via natural language commands.

CNN's Fear & Greed index for the US stock market: current score and rating, the seven component indicators, and about a year of daily history. Go standard library only, no API key required.