Simple Rust MCP Server

Context7 MCP Server -- Up-to-date code documentation for LLMs and AI code editors

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.

MCP server to provide Figma layout information to AI coding agents like Cursor

Write notes to Flomo

GBOX provides environments for AI Agents to operate computer and mobile devices. Mobile Scenario: Your agents can use GBOX to develop/test android apps, or run apps on the Android to complete various tasks(mobile automation). Desktop Scenario: Your agents can use GBOX to operate desktop apps such as browser, terminal, VSCode, etc(desktop automation). MCP: You can also plug GBOX MCP to any Agent you like, such as Cursor, Claude Code. These agents will instantly get the ability to operate computer and mobile devices.

Retrieving and analyzing issues from Sentry.io

A Model Context Protocol Server connector for Perplexity API, to enable web search without leaving the MCP ecosystem.

An MCP server implementation for retrieving information from the AWS Knowledge Base using the Bedrock Agent Runtime.

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

GitLab API, enabling project management

Location services, directions, and place details

Secure file operations with configurable access controls

Let AI automatically analyze the site. Not limited to site monitoring, competitive product analysis, automatic keyword mining, n8n integration, etc.

NetForensicMCP V2.1 is a Model Context Protocol (MCP) server designed to empower Large Language Models (LLMs) with advanced offline network traffic analysis and threat intelligence capabilities. Built on top of Wireshark's tshark, NetForensicMCP provides comprehensive PCAP analysis tools for cybersecurity professionals, threat hunters, and network forensics investigators.

A Model Context Protocol (MCP) server that integrates with Jina AI Search Foundation APIs.

A Model Context Protocol server that provides access to Redis databases. This server enables LLMs to interact with Redis key-value stores through a set of standardized tools.

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

Automatically create a remote browser to complete your specified tasks, developed based on Browser Use + Sandbox. 自动创建一个远程浏览器，完成你指定的任务，基于Browser Use + Sandbox开发。

虎嗅官方 MCP 服务，现提供工具功能为精选原创视频推荐，视频涵盖: 美食科普类「赛博食录」、时尚消费类「三亿世代实验室」、健康医疗类「九叶刀」、汽车科技类「暗信号」、商业财经「并非虎扯」、前沿科技类「虎学研究」、人物对话类「关关过」。视频内容实时同步更新。 后续将提供图文资讯类等工具，敬请关注。

This Snowflake MCP server provides tooling for Snowflake Cortex AI features, bringing these capabilities to the MCP ecosystem. When connected to an MCP Client (e.g. Claude for Desktop, fast-agent, Agentic Orchestration Framework), users can leverage these Cortex AI features. The MCP server currently supports the below Cortex AI capabilities: Cortex Search: Query unstructured data in Snowflake as commonly used in Retrieval Augmented Generation (RAG) applications. Cortex Analyst: Query structured data in Snowflake via rich semantic modeling. Cortex Agent: Agentic orchestrator across structured and unstructured data retrieval

One API for Search, Crawling, and Sitemaps

天气

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

MCP server for interacting with Neon Management API and databases

The QuantConnect MCP Server is a bridge for AIs (such as Claude and OpenAI o3 Pro) to interact with our cloud platform. When equipped with our MCP, the AI can perform tasks on your behalf through our API such as updating projects, writing strategies, backtesting, and deploying strategies to production live-trading. To get your user Id and API token, see Request API Token (https://www.quantconnect.com/docs/v2/cloud-platform/community/profile#09-Request-API-Token). Our MCP server is multi-platform capable. The options are `linux/amd64` for Intel/AMD chips and `linux/arm64` for ARM chips (for example, Apple's M-series chips).

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"

百度地图核心API现已全面兼容MCP协议，是国内首家兼容MCP协议的地图服务商。

PyGhidra-MCP - Ghidra Model Context Protocol Server pyghidra-mcp is a command-line Model Context Protocol (MCP) server that brings the full analytical power of Ghidra, a robust software reverse engineering (SRE) suite, into the world of intelligent agents and LLM-based tooling. It bridges Ghidra’s ProgramAPI and FlatProgramAPI to Python using pyghidra and jpype, then exposes that functionality via the Model Context Protocol. MCP is a unified interface that allows language models, development tools (like VS Code), and autonomous agents to access structured context, invoke tooling, and collaborate intelligently. Think of MCP as the bridge between powerful analysis tools and the LLM ecosystem. With pyghidra-mcp, Ghidra becomes an intelligent backend—ready to respond to context-rich queries, automate deep reverse engineering tasks, and integrate into AI-assisted workflows. Yet another Ghidra MCP? Yes, the original ghidra-mcp is fantastic. But pyghidra-mcp takes a different approach: 🐍 No GUI required – Run entirely via CLI for streamlined automation and scripting. 🔁 Designed for automation – Ideal for integrating with LLMs, CI pipelines, and tooling that needs repeatable behavior. ✅ CI/CD friendly – Built with robust unit and integration tests for both client and server sessions. 🚀 Quick startup – Supports fast command-line launching with minimal setup. 📦 Project-wide analysis – Enables concurrent reverse engineering of all binaries in a Ghidra project 🤖 Agent-ready – Built for intelligent agent-driven workflows and large-scale reverse engineering automation. 🔍 Semantic code search – Uses vector embeddings (via ChromaDB) to enable fast, fuzzy lookup across decompiled functions, comments, and symbols—perfect for pseudo-C exploration and agent-driven triage.