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Enables semantic search and retrieval of MCP (Model Context Protocol) documentation using Redis-backed embeddings, allowing users to query and access documentation content through natural language.

Converts DOCX files to Markdown with formatting preservation and image extraction, and provides image analysis tools for document processing workflows.

Enables parsing and extraction of content from various document formats (PDF, Word, Excel, PowerPoint) into Markdown format using the Niutrans document API.

An intelligent document processing system that automatically classifies, extracts information from, and routes business documents using the Model Context Protocol (MCP).

A multi-format MCP server that enables reading and generating Office, PDF, text, EPUB, and presentation documents. It provides unified tools for document processing and creation through AI assistants.

Efficiently delivers project documentation to AI agents like Claude on-demand, optimizing token usage by loading context only when needed. Supports document retrieval, listing, and keyword search with security features.

Enables LLMs to read .NET assemblies as C# by providing tools to list types, decompile types, decompile assemblies, and search decompiled source.

MCP Drive

This repository contains a project to implement mcp server in spring for google drive

MCP Eda Server

Server for EDA Tools, Duke University

Enables storing and retrieving information using vector embeddings with semantic search capabilities. Integrates with the AI Embeddings API to automatically generate embeddings for content and perform similarity-based searches through natural language queries.

MCPE Server Proxy

This helps with joining MCPI servers on MCPE

MCP Experiments

Experiments with MCP server and clients.

MCP Fashion Server

AI 기반 여성 의류 쇼핑몰 콘텐츠 자동화 시스템

Fetches web pages and converts them to clean, readable markdown format by extracting main content while removing navigation, ads, and other non-essential elements to minimize token usage.

A beginner MCP server that enables Claude to read local text, CSV, and Markdown files. Built as a learning project to understand how to connect AI to local file systems using the MCP protocol.

Mcpfinder MCP

MCPfinder 🔧🤖 is a service that enables LLMs, running through client applications that support the MCP protocol, to dynamically discover and access new tools, features, and capabilities. When a user requests functionality the AI doesn’t have, it can simply ask MCP Finder to locate relevant MCP servers, expanding its toolset in real time.

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.

MCP Gateway 79fcdf96

MCP Gateway and Registry

Provides Google Search functionality for AI models using Gemini's built-in Grounding with Google Search feature, returning real-time web search results with source citations.

Provides semantic search and management of shared documentation using ChromaDB and OpenAI embeddings. It enables users to query local documents by meaning, list files, and read content through natural language tools.