"A system for semantically searching local Markdown files" matching MCP servers:

Enables AI assistants to access and inspect local files within a specified sandbox root.

Provides a local MCP server for AI-powered web crawling on Windows, enabling agents to directly crawl and extract web content without requiring WSL.

Enables local web crawling and scraping through MCP, providing tools to fetch pages as Markdown, extract structured data with CSS selectors, and capture full-page screenshots while managing a shared browser instance.

Generates test files locally (images, PDFs, CSVs, corrupted files, etc.) from natural language prompts, with configurable sizes and safety limits.

A customizable Model Context Protocol server implementation that enables AI models to interact with external tools including weather queries, Google search, and camera control functionality.

A local vector database system that provides LLM coding agents with fast, efficient semantic search capabilities for software projects via the Message Control Protocol.

Splits Markdown documents into hierarchical sections with parent-child and sibling relationships, enabling structured document access for AI assistants.

Enables reading and optionally editing existing Markdown files under a configured root folder, including section-level queries, overwrites, appends, deletions, and front matter management, over stdio with no network dependencies.

Translates project README files into multiple languages via MCP server or standalone pipeline, using local LM Studio models for translation, critique, and revision.

Enables AI agents to search and query the public DOJ Epstein Files release across 20 databases, resolve EFTA numbers to official DOJ PDFs, and cross-check viral claims against a fact-checked registry.

MCP server that converts PDF, video, web, and audio inputs into structured Markdown notes with support for checkpointing, batch processing, and Obsidian integration.

MCP server for bidirectional Markdown-to-Confluence sync, enabling download and publish of Confluence pages as Markdown with images, frontmatter tracking, and dry-run safety.

Provides an intelligent, graph-based memory system for LLM agents using the Zettelkasten principle, enabling automatic note construction, semantic linking, memory evolution, and autonomous graph maintenance with background optimization processes.

Write your resume in Markdown and export to PDF with AI assistance, using a built-in stylesheet and tools for conversion.

A generic Markdown vault MCP server with FTS5 full-text search, semantic vector search, frontmatter-aware indexing, incremental reindexing, and non-markdown attachment support that exposes search, read, write, and edit tools.

A Model Context Protocol (MCP) server that provides a local-first RAG engine for your markdown documents. It uses a file-based Milvus vector database to index your notes, enabling LLMs to perform semantic search and retrieve relevant content from your local files.

Converts XMind mind map files into structured Markdown documents, preserving hierarchy and optionally including metadata.

Enables MCP clients like Claude to query Chinese A-share market data, including K-line charts with forward/backward adjustment, limit-up and limit-down pools, per-stock fund flows, index quotes, and stock news, with automatic symbol normalization and retry handling for throttled data sources.

Provides A-share (Chinese stock market) quantitative analysis through tools for stock screening, northbound capital flow tracking, dragon-tiger list analysis, margin trading, sector analysis, technical indicators, IPO info, and limit-up/down statistics using akshare data.

Python MCP server for programmatic access to markdown-based knowledge vaults, enabling AI assistants to browse, read, search, update, and manage notes, tasks, and projects.