Cross-System Agent Communication MCP Server

A short URL management client based on MCP (Model Context Protocol) protocol, providing complete short URL generation, management, and statistics functionality for AI assistants.

The TwelveLabs MCP Server provides seamless integration with the TwelveLabs platform. This server enables AI assistants and applications to interact with TwelveLabs powerful video analysis capabilities through a standardized MCP interface.

Flag features directly from chat in your code editor, including VS Code, Cursor, Windsurf, Claude Code—any IDE with MCP support.

A Model Context Protocol (MCP) server for image generation and manipulation using fal.ai's Stable Diffusion model.

Zhipu Web Search MCP Server is a search engine specifically designed for large models. It integrates four search engines, allowing users to flexibly compare and switch between them. Building upon the web crawling and ranking capabilities of traditional search engines, it enhances intent recognition capabilities, returning results more suitable for large model processing (such as webpage titles, URLs, summaries, site names, site icons, etc.). This helps AI applications achieve "dynamic knowledge acquisition" and "precise scenario adaptation" capabilities.

BlenderMCP connects Blender to Claude AI through the Model Context Protocol (MCP), allowing Claude to directly interact with and control Blender. This integration enables prompt assisted 3D modeling, scene creation, and manipulation.

Channel management and messaging capabilities

A Serper MCP Server

Arch MCP provides three main capabilities: - 🔍 Resources - URI-based access to Arch Wiki, AUR packages, official repos, and installed packages - 🛠️ Tools - Search, analyze, and securely install packages with built-in safety checks - 📋 Prompts - Guided workflows for troubleshooting, security audits, and dependency analysis

MCP server for Terraform — automatically validates, secures, and estimates cloud costs for Terraform configurations. Integrates with any Model Context Protocol (MCP) client (e.g. Claude Desktop or other MCP-compatible AI assistants).

https://github.com/enuno/unifi-mcp-server

Create a remote sandbox that can execute code/run commands/upload and download files. 创建远程沙盒，可以执行代码/运行命令/上传下载文件

基于Anduin2017 / HowToCook （程序员在家做饭指南）的mcp server，帮你推荐菜谱、规划膳食，解决“今天吃什么“的世纪难题； Based on Anduin2017/HowToCook (Programmer's Guide to Cooking at Home), MCP Server helps you recommend recipes, plan meals, and solve the century old problem of "what to eat today"

Web and local search using Brave's Search API

A Model Context Protocol (MCP) server providing solutions for Constraint Satisfaction Problems (CSP) and Linear Programming (LP). Built on the gurddy optimization library, it supports solving a variety of classic problems through two MCP transports: stdio (for IDE integration) and HTTP/SSE (for web clients). 🚀 Quick Start (Stdio): pip install gurddy_mcp then configure in your IDE 🌐 Quick Start (HTTP): docker run -p 8080:8080 gurddy-mcp or see deployment guide 📦 PyPI Package: https://pypi.org/project/gurddy_mcp

An MCP server implementation that provides a tool for dynamic and reflective problem-solving through a structured thinking process.

An MCP service designed for deploying HTML content to EdgeOne Pages and obtaining an accessible public URL.

PlusE is the Ultra Data Source for Your Trading AI—a revolutionary Model Context Protocol (MCP) service that transforms noisy market data into AI-ready trading intelligence. Old-school raw historical price is out, our HTTP Streamable MCP service is the best way to power trading AI. With pre-digested real-time financial insights delivered directly to your AI models via HTTP Streamable MCP, you can make smarter trading AI — in 5 minutes, no complex pipelines required. Unlike traditional financial data providers that require custom API integrations, PlusE uses the standard Model Context Protocol delivered via HTTP to seamlessly connect financial data tools directly to your AI models. Our service preprocesses, filters, and condenses massive financial datasets into high-density data abstractions. These pre-digested insights eliminate information overload and enable your trading AI to make faster, more accurate decisions.