MCP Go is a server-side framework for the Model Context Protocol (MCP) implemented in Go, used to connect LLM applications with external data sources and tools. It provides core functions such as resource management, tool invocation, and prompt templates, and supports session management and middleware extension.

Documentation for the integration of the Unreal Engine Model Context Protocol (MCP), helping to understand, set up, and use the MCP system.

mcp-golang is an unofficial Go implementation of the Model Context Protocol library, supporting the rapid construction of MCP servers and clients, and providing features such as type safety, low code volume, modularity, and two-way communication.

MCP Atlassian is a Model Context Protocol server designed for Atlassian products (Confluence and Jira), supporting both cloud and on-premises deployments and providing AI assistant integration functions.

This project implements an MCP server for the Notion API, allowing access to and operation of Notion content through the model context protocol, supporting functions such as searching, commenting, and adding pages.

The AWS MCP Servers are a set of dedicated servers based on the Model Context Protocol, offering various AWS-related functions, including document retrieval, knowledge base query, CDK best practices, cost analysis, image generation, etc., aiming to enhance the integration of AI applications with AWS services through a standardized protocol.

Awesome - MCP - ZH is a collection of MCP (Model Context Protocol) resources tailored for Chinese users, including basic introductions, usage guides, client, server, and community resources to help users quickly get started with MCP.

Klavis AI is an open-source project that provides a simple and easy-to-use MCP (Model Context Protocol) service on Slack, Discord, and Web platforms. It includes various functions such as report generation, YouTube tools, and document conversion, supporting non-technical users and developers to use AI workflows.

The Supabase MCP Server is a tool that connects Supabase projects with AI assistants. It standardizes the interaction between large language models (LLMs) and external services through the Model Context Protocol (MCP), enabling functions such as database management, configuration acquisition, and data querying.

UnityMCP is a Unity editor plugin that implements the Model Context Protocol (MCP), providing seamless integration between Unity and AI assistants, including real - time state monitoring, remote command execution, and log functions.

AbletonMCP is an integration tool that connects Ableton Live and Claude AI. It enables two - way communication via the Model Context Protocol (MCP), allowing AI to directly control and operate Ableton Live for music creation and production.

Claude Context is an MCP plugin that provides in - depth context of the entire codebase for AI programming assistants through semantic code search. It supports multiple embedding models and vector databases to achieve efficient code retrieval.

Airweave is an open - source context retrieval layer for AI agents and RAG systems. It connects and synchronizes data from various applications, tools, and databases, and provides relevant, real - time, multi - source contextual information to AI agents through a unified search interface.

iMCP is a macOS application that connects users' digital lives through AI. It supports interaction with clients such as Claude Desktop via the Model Context Protocol (MCP), providing various functions including calendar, contacts, location, maps, messages, reminders, and weather.

The MCP-Framework is a TypeScript-based framework for elegantly building Model Context Protocol (MCP) servers. It provides an out-of-the-box architecture, supports automatic directory discovery of tools, resources, and prompts, and has multiple transmission methods and type-safe features.

The Apify MCP Server is a tool based on the Model Context Protocol (MCP) that allows AI assistants to extract data from websites such as social media, search engines, and e-commerce through thousands of ready-to-use crawlers, scrapers, and automation tools (Apify Actors). It supports OAuth and Skyfire proxy payment and can be integrated into MCP clients such as Claude and VS Code through HTTPS endpoints or local stdio.

Acemcp is an MCP server for codebase indexing and semantic search, supporting automatic incremental indexing, multi-encoding file processing, .gitignore integration, and a Web management interface, helping developers quickly search for and understand code context.

Supermemory is an AI-driven memory engine designed to provide contextual knowledge for LLMs by integrating personal data, enabling intelligent management and retrieval of information.

PG-MCP is a model context protocol server designed for PostgreSQL databases, providing APIs for AI agents to discover, connect, query, and understand databases. It supports multi - database connection, rich catalog information, and query explanation functions.

FastAPI-MCP is a library that exposes FastAPI endpoints as Model Context Protocol (MCP) tools, with built-in authentication, supporting flexible deployment and ASGI transmission.

MCP Unity is a Unity Editor extension that implements the Model Context Protocol, allowing AI assistants to interact with Unity projects and providing a bridge between Unity and the Node.js server.

The Firecrawl MCP Server is a Model Context Protocol server integrating Firecrawl's web - scraping capabilities, providing rich web - scraping, searching, and content - extraction functions.

MCP Unity is a Unity Editor extension that implements the Model Context Protocol. It bridges the interaction between AI assistants and Unity projects through a Node.js server, providing functions such as menu execution, object selection, and component update.

Zen MCP is a multi-model AI collaborative development server that provides enhanced workflow tools and cross-model context management for AI coding assistants such as Claude and Gemini CLI. It supports seamless collaboration of multiple AI models to complete development tasks such as code review, debugging, and refactoring, and can maintain the continuation of conversation context between different workflows.

The MiniMax Model Context Protocol (MCP) is an official server that supports interaction with powerful text-to-speech, video/image generation APIs, and is suitable for various client tools such as Claude Desktop and Cursor.

Context7 MCP is a service that provides real-time, version-specific documentation and code examples for AI programming assistants. It is directly integrated into prompts through the Model Context Protocol to solve the problem of LLMs using outdated information.

MoltBrain is a long-term memory layer plugin designed for OpenClaw, MoltBook, and Claude Code, capable of automatically learning and recalling project context, providing intelligent search, observation recording, analysis statistics, and persistent storage functions.

This is a curated list of Web3 Model Context Protocol (MCP) servers, covering multiple categories such as chain interaction, trading, DeFi, market data, tools, and social. MCP is an open protocol that standardizes how applications provide context to LLMs, similar to the USB - C port for AI applications. DeMCP is the first decentralized MCP network, focusing on providing self - developed and open - source MCP services for agents, supporting cryptocurrency payments, and redefining the security and reliability of MCP by combining TEE and blockchain registries.

The 302AI BrowserUse MCP Server is an AI-based browser automation server that enables natural language control of browsers and web research through the Model Context Protocol (MCP).

The Kubectl MCP Tool is a Kubernetes interaction tool based on the Model Context Protocol (MCP), allowing AI assistants to interact with Kubernetes clusters using natural language.

LINE Bot MCP Server is a service that implements the Model Context Protocol (MCP) for connecting AI agents to LINE official accounts, supporting functions such as pushing text and rich - media messages, broadcasting messages, and retrieving user profiles.

The GitLab MCP server is a project based on the Model Context Protocol that provides a comprehensive toolset for interacting with GitLab accounts, including code review, merge request management, CI/CD configuration, and other functions.

A Bilibili video search server based on the Model Context Protocol (MCP), providing API interfaces to support video content search, paginated queries, and video information return, including LangChain call examples and test scripts.

A Redis database operation service based on the Model Context Protocol, providing various Redis command tools

The MCP MongoDB Server is a model context protocol service that allows LLMs to interact with MongoDB databases, providing functions such as collection schema checking, query execution, and intelligent ID handling, and supporting read - only mode and security configuration.

MiniMax's official Model Context Protocol (MCP) server supports interactions with APIs such as text-to-speech, video/image generation.

Smithery CLI is a command-line tool for managing Model Context Protocol (MCP) servers, supporting multiple AI clients and providing functions for installing, uninstalling, viewing, and running MCP servers.

Security Detections MCP is a server based on the Model Context Protocol that allows LLMs to query a unified security detection rule database covering Sigma, Splunk ESCU, Elastic, and KQL formats. The latest version 3.0 is upgraded to an autonomous detection engineering platform that can automatically extract TTPs from threat intelligence, analyze coverage gaps, generate SIEM-native format detection rules, run tests, and verify. The project includes over 71 tools, 11 pre-built workflow prompts, and a knowledge graph system, supporting multiple SIEM platforms.

Godot MCP is a Model Context Protocol server designed for the Godot game engine, providing interaction functions with the Godot editor and projects.

The iOS Simulator MCP Server is a tool for interacting with the iOS simulator via the Model Context Protocol (MCP), supporting functions such as obtaining simulator information, controlling UI interactions, and checking UI elements.