microsoft/markitdown
MarkItDown is a Python tool that converts various file formats into Markdown and integrates with LLM applications via an MCP server for enhanced text analysis and document processing.
Awesome MCP › Other MCP Servers
deedy5/ddgs
DDGS (Dux Distributed Global Search) is a metasearch library designed to aggregate search results from multiple diverse web search services into a unified interface. It supports various types of searches including text, images, videos, news, and books, making it a versatile tool for retrieving information from the web. The library provides an API server with integration for the Model Context Protocol (MCP), enabling AI assistance and interaction through HTTP and Server-Sent Events (SSE) transports. This integration allows users to perform searches via MCP endpoints, facilitating seamless communication and data retrieval for AI applications. The project supports a wide range of search backends for different content types. For text searches, it includes popular engines like Bing, Brave, DuckDuckGo, Google, Grokipedia, Mojeek, Yandex, Yahoo, and Wikipedia. Image and video searches are primarily supported through DuckDuckGo, while news searches utilize Bing, DuckDuckGo, and Yahoo. Book searches are available through Annasarchive. This extensive backend support ensures comprehensive search results from multiple sources. DDGS offers both a command-line interface (CLI) and a Python library interface, making it accessible for various user preferences and integration scenarios. The DDGS class is lazy-loaded and provides methods such as text(), images(), videos(), news(), and books() to perform specific types of searches with customizable parameters like region, safesearch level, time limits, maximum results, and backend selection. The API server can be easily deployed using Docker Compose or a shell script, providing endpoints for MCP and API documentation, along with health checks. The project emphasizes flexibility and configurability, allowing users to specify proxies, timeouts, and verification options for HTTP clients. Overall, DDGS is a powerful metasearch tool that leverages multiple search engines and integrates with MCP to provide enhanced search capabilities for AI and other applications, making it a valuable resource for developers and researchers needing aggregated search results.
https://github.com/deedy5/ddgs
Also in Other MCP Servers
punkpeye/awesome-mcp-servers
A curated collection of Model Context Protocol (MCP) servers that enable AI models to securely interact with local and remote resources through standardized server implementations.
modelcontextprotocol/servers
The Model Context Protocol Servers repository offers reference implementations and third-party integrations that demonstrate how MCP enables Large Language Models to securely access and interact with diverse tools and data sources.
koala73/worldmonitor
World Monitor is an AI-powered, real-time global intelligence dashboard aggregating news and monitoring geopolitical and infrastructure data for unified situational awareness.
headroomlabs-ai/headroom
Headroom is a context compression layer for AI agents, reducing token usage by 60-95% while preserving accuracy, implemented as a library, proxy, and MCP server.
diegosouzapw/OmniRoute
OmniRoute is a free AI gateway that connects various AI tools and models from over 230 providers through a single endpoint, featuring token compression, smart auto-fallback, and support for Model C...
rohitg00/ai-engineering-from-scratch
This comprehensive curriculum teaches AI engineering from scratch, focusing on building AI algorithms, agents, and MCP servers hands-on, covering everything from mathematical foundations to autonom...
every-app/open-seo
Open source, self-hostable SEO platform that exposes its keyword, rank, backlink and site-audit data to AI agents through an MCP server and a set of companion agent skills.