The YouTube MCP Server is a standardized interface implementation that allows AI language models to interact with YouTube content through protocols, providing functions such as video information retrieval, subtitle management, channel and playlist management.

The Linkup MCP Server is a server based on the Model Context Protocol, providing real-time web search and web page content scraping functions through the Linkup API, enabling AI assistants to access the latest information on the Internet.

Crawl4AI MCP Server is an intelligent information acquisition server based on the MCP protocol, which provides multi - engine search and optimized web content extraction functions for AI systems, and converts web pages into a format suitable for LLM processing.

The Pulse CN MCP Server is an MCP protocol server that obtains real-time Chinese Internet popular content. It supports hot search data from 18 platforms such as Weibo and Today's Headlines, providing the latest Chinese trend information for AI models.

Civitai MCP Server is a model context protocol service that provides comprehensive access to AI models on the Civitai platform, including functions such as searching for, browsing models, viewing creator information, and browsing generated content.

The PDF Reader MCP service provides AI agents with a secure and flexible function to extract content from PDF files, including text, metadata, and page count information. It supports local and remote PDF files and is easy to integrate into the MCP environment.

The YouTube MCP Server is a service that implements the Model Context Protocol (MCP). It provides a standardized interface for AI language models to interact with YouTube content, supporting functions such as video information retrieval, subtitle management, channel and playlist operations, etc.

GEO Analyzer is a tool for analyzing the visibility of content in AI searches. By evaluating key indicators such as statement density, information density, answer pre - positioning, and semantic triples in the content, it helps optimize the content to increase the probability of being cited by AI systems such as ChatGPT and Claude.

This project is a Reddit service interface based on the Model Context Protocol (MCP), implemented through the Python Reddit API Wrapper (PRAW), which allows AI assistants to access and interact with Reddit content. The project provides functions such as user information analysis, getting popular posts, community statistics, and viewing trending sub - forums, and supports authenticated users to post and comment.

This project implements a Model Context Protocol (MCP) server that enables AI assistants like Claude to interact with Substack newsletters, articles, and authors through a standardized interface. It is based on the Substack API library and provides functions such as getting article content, searching for newsletters, and querying author information.

Claude Deep Research is a research server based on the MCP protocol. It provides comprehensive research capabilities for AI assistants like Claude, integrating web and academic search functions, and supporting multi - source information acquisition, content extraction, and structured analysis.

The MCP Server is a server that provides AI assistants with the ability to perform web searches and access web pages, supporting the secure acquisition of real-time information and the processing of web page content.

An MCP server developed in Go, supporting SSE and stdio operation modes. It provides functions for querying Bilibili personal information, following lists, and video search, and helps AI select personalized video content.

This project aims to provide access to the content of the Swedish National Archives (Riksarkivet) through multiple API interfaces (such as OAI - PMH, IIIF, and Search API), including functions such as searching for records, obtaining collection information, downloading images, etc., and exploring the real - time handwritten text recognition (HTR) process.

mcp - searxng is an MCP server example designed for AI agents, which implements the external information search function through the open - source meta - search engine SearXNG. The project demonstrates how to integrate SearXNG and Microsoft's markdownify tool to convert web page content into Markdown - formatted text and communicate with MCP clients via the SSE protocol.

Fetcher MCP is a web content scraping server based on the Playwright headless browser, which uses AI technology to efficiently obtain web information.

The Context Engineering MCP Platform is an AI context management and optimization platform that designs, manages, and optimizes the input information of AI models through a systematic approach, realizing the engineering of prompt engineering. The platform provides functions such as intelligent analysis engines, optimization algorithms, and template management, significantly improving AI response quality, reducing API costs, and supporting multimodal content processing.

An MCP server developed in Go, supporting SSE and stdio operation modes, providing functions such as Bilibili personal information query, latest following list, and video search, and facilitating AI to select personalized video content.

The Copus MCP server is a server based on the model context protocol that allows AI assistants to search for and retrieve human-curated content recommendations from the Copus platform. Copus is a discovery platform where real people recommend and explain the value of content, different from algorithm-driven search results. The server provides tools for searching curated content and obtaining detailed information, and is compatible with multiple AI platforms that support MCP.

ghcontext is a tool that connects GitHub with large language models. It provides real-time repository information, including API documentation, README content, and code structure, for AI assistants through the Model Context Protocol (MCP), ensuring that the information obtained by AI is always up-to-date.

This project is an MCP server tool designed to enable AI agents to search for content and information on external websites through the SearXNG service.

What2Watch MCP is a service that provides real - time entertainment content discovery capabilities for AI assistants. It integrates program information from thousands of TV channels and streaming platforms and can provide personalized recommendations based on user preferences, mood, and time.

The Radio France Podcast Explorer MCP service is a model control protocol server that allows AI assistants to search and browse Radio France podcasts, audio replays, and other content. It provides functions such as topic - based podcast search, radio program information retrieval, and categorical content browsing.

GitLab-MCP-Server is a model context protocol server integrated with GitLab, providing functions to retrieve pipeline failure information, merge request comments, and change content to assist AI assistants in code review and issue repair.

A Model Context Protocol (MCP) server designed for BigQuery that helps AI agents obtain database content information to optimize SQL queries.

An MCP server implementation based on the YouTube Data API, providing a standardized interface for AI language models to access YouTube content, including functions such as video information, subtitle management, channel analysis, and trend analysis.

An MCP server specifically designed to obtain information from the Guozaoke forum. It allows you to access forum topics and content through an AI assistant, and supports functions such as obtaining the latest topics, today's popular topics, and topic details.

A multi - agent deep research system based on the MCP protocol, which uses CrewAI to coordinate three professional AI agents for web search, information analysis, and content creation, supporting local AI processing and a web interface.