A collection of official Microsoft MCP servers, providing AI assistant integration tools for various services such as Azure, GitHub, Microsoft 365, and Fabric. It supports local and remote deployment, helping developers connect AI models with various data sources and tools through a standardized protocol.

Genkit is an open-source framework for building AI-driven applications, providing Node.js and Go libraries, supporting the integration of multiple AI models and vector databases, and including development tools and a plugin ecosystem.

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.

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.

An MCP server that integrates AI models with WinDbg/CDB for analyzing Windows crash dump files and remote debugging, supporting natural language interaction to execute debugging commands.

Provide MCP server support for Nuxt/Vite applications to help models better understand the application structure.

OpenDia is an open - source browser extension tool that allows AI models to directly control the user's browser, perform automated operations using existing login status, bookmarks and other data, support multiple browsers and AI models, and focus on privacy protection.

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.

A Python-based MCP Server that provides advanced to-do list management and content organization functions through the Notion API, enabling seamless integration between AI models and Notion.

The Notion MCP server is a protocol service that connects AI models to the Notion workspace through the official SDK, providing a comprehensive set of Notion operation tools.

Wren Engine is a semantic engine designed for MCP clients and AI agents, providing semantic layer support to enable AI to accurately understand enterprise data models and business logic. It supports multiple data sources and is embedded in MCP clients to ensure the accuracy and governance of data interaction.

Blender MCP VXAI is a powerful integration tool that allows users to control Blender through natural language to create and modify 3D models, animations, and scenes. It simplifies complex operations and supports real-time export to projects.

MemoryMesh is a knowledge graph server designed for AI models, focusing on text role - playing games and interactive narratives. It helps AI maintain consistent and structured memory in conversations through dynamic schema definition and automatic tool generation, enabling a richer and more dynamic interactive experience.

Jinni is an efficient tool for providing project context to large language models. It overcomes the limitations of reading files one by one by integrating relevant files and their metadata.

The AI Infrastructure Agent is an intelligent system that allows users to manage AWS cloud resources through natural language commands. It uses AI models to convert user requirements into executable AWS operations and provides web dashboards, state management, and security protection functions.

LLM Context is a tool that helps developers quickly inject code/text project content into the chat interface of large language models, supporting intelligent file selection and multiple integration methods.

This project provides support for Model Context Protocol (MCP) tool calls for LangChain, enabling interaction with AI models through the MCP toolkit, such as file reading and summary generation.

MemoryMesh is a knowledge graph server designed for AI models, focusing on text RPGs and interactive narratives, helping AI maintain structured memory across conversations.

mcp-hfspace is an MCP server that connects to Hugging Face Spaces, supporting various AI functions such as image generation, speech processing, and visual models, simplifying the integration with Claude Desktop.

MCPEngine is a production-grade implementation of the Model Context Protocol (MCP), providing standardized interfaces for large language models (LLMs). It supports functions such as OAuth authentication, resource management, and tool invocation, aiming to become the 'REST of the LLM world' framework.

An implementation of the Model Context Protocol (MCP) in Java and the Spring framework, providing a standardized interface for interacting with AI models and supporting synchronous/asynchronous communication modes.

A generative AI support plugin for Unreal Engine that integrates multiple cutting - edge LLM/GenAI model APIs, providing AI integration layer support in game development, including chat and structured output functions for models such as OpenAI, Claude, and Deepseek, and supporting the Model Control Protocol (MCP) to achieve advanced functions such as scene object control and blueprint generation.

MCP service that provides A-share data for large models

MCP2Lambda is an MCP protocol server that runs AWS Lambda functions as tools for large language models (LLMs). AI models can call Lambda functions to access private resources and AWS services without code modification.

Notebook Intelligence (NBI) is an AI coding assistant and extensible AI framework designed for JupyterLab. It supports models from GitHub Copilot and other LLM providers, including local Ollama models. It significantly enhances productivity through features such as code generation, auto - completion, and chat interfaces, and supports the integration of Model Context Protocol (MCP) services.

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 Alpaca MCP server is a model context protocol (MCP) service that implements the Alpaca trading API, allowing large language models to interact with the Alpaca trading system through natural language, supporting stock/options trading, portfolio management, and real-time market data acquisition.

HWP-MCP is a protocol service that enables AI models to control HWP documents, supporting document creation, editing, and automation processing.

MCP2Lambda is an MCP server that allows AWS Lambda functions to be used as tools for large language models (LLMs) without modifying the code. It builds a bridge between AI models and Lambda functions through the Model Context Protocol (MCP), enabling models to access private resources and perform custom operations.

An MCP server project that enables interaction between Claude Desktop and Google Gemini AI models

FreeCAD MCP is a plugin for controlling FreeCAD through Claude Desktop, supporting various design functions such as creating 3D models from 2D drawings.

The Rails MCP Server is a Model Context Protocol server implemented in Ruby, providing a standard interface for Rails projects to interact with large language models.

WireMCP is an MCP server that provides real-time network traffic analysis capabilities for large language models (LLMs). It realizes data capture, threat detection, and network diagnosis by integrating the Wireshark tool.

A knowledge graph memory server implemented in Swift, providing persistent memory functions for large - language models

XiYan MCP Server is a model context protocol server based on XiYan-SQL that supports querying databases through natural language and provides options for integrating multiple LLM models and local deployment.

This project implements functions similar to Claude Code through the MCP protocol, providing tools for code understanding, modification, and command execution. It supports multiple models and Jupyter notebook operations, and has security control and development expansion capabilities.

The Image Gen MCP Server is a general AI image generation service that provides cross - platform and multi - model image generation capabilities for various LLM chatbots through the Model Context Protocol (MCP) standard protocol. It supports multiple image models from OpenAI and Google, enabling seamless conversion from text conversations to visual content.

An MCP server for interacting with macOS Apple calendars, providing a standardized interface for AI models to access and manipulate calendar data.

The Scrapezy MCP Server is a service that enables AI models to extract structured data from websites and supports data scraping through tools such as Claude.

MCPfinder is a local server tool that provides dynamic capability expansion for AI agents. By searching for and installing toolkits compatible with the MCP protocol, language models can obtain new functions on demand.