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.

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.

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.

XiYan MCP Server is a Model Context Protocol server based on XiYan - SQL, which supports querying databases through natural language, provides multiple LLM model configurations and database connection methods, and is suitable for local or remote deployment.

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 is an automated deployment script project for installing and configuring multiple Model Context Protocol (MCP) robot services on a Windows system, including functions such as file system, GitHub, search, and memory management, and provides detailed installation guides and troubleshooting methods.

The IBM i MCP server is a server based on the Model Context Protocol, providing SQL tools, monitoring, and automation functions for the IBM i system, supporting multiple client integrations and containerized deployment

A Model Context Protocol (MCP) server template project based on TypeScript, providing a structured, maintainable and extensible framework, including implementation examples of tools, resources and prompts, supporting configuration management, logging, error handling and containerized deployment.

The Railway MCP Server is a service based on the Model Context Protocol (MCP) for managing the infrastructure of Railway.app through natural language, including deploying services, managing variables, and monitoring deployments.

This project implements a server based on the Model Context Protocol (MCP) for deploying web applications to AWS serverless infrastructure, supporting automatic deployment of front - end, back - end, and full - stack applications.

The Quickchat AI MCP server allows users to integrate Quickchat AI agents into various AI applications, such as Claude Desktop and Cursor, and achieve seamless connection through the Model Context Protocol (MCP). Users can easily configure and manage MCP services through the Quickchat AI dashboard without complex deployment.

The Coolify MCP Server is a model context protocol server integrated with the Coolify API, providing functions such as team management, server management, service lifecycle management, and application deployment.

A Model Context Protocol (MCP) server for Rollbar, providing a variety of tools to query Rollbar project data, such as getting error details and deployment records.

A Python template project for quickly building a Model Context Protocol (MCP) server, which provides registration and exposure functions for tools and tips and supports multiple deployment methods.

An OAuth2 authorization server project based on Spring Boot 3 and Java 24, supporting GraalVM native images, CRaC checkpoint restoration, local AI model testing, and Docker deployment.

This project is a server - side implementation based on the Model Context Protocol (MCP) for connecting to the GraphQL API to access policy data. It is built using the Python SDK and GQL library and supports rapid deployment through the uv tool.

MCP Email Verify is a lightweight server based on the Model Context Protocol (MCP) for real-time verification of email address validity. It checks email format, domain name validity, and deliverability through AbstractAPI and is suitable for integration into AI applications such as Claude Desktop. The project offers simple deployment and MCP compatibility, supporting Python environments.

A Nix-based Model Control Protocol (MCP) server configuration framework that provides modular configuration and pre-built server packages, supporting secure deployments and reproducible builds.

The Nextcloud MCP Server is a tool rewritten in TypeScript that allows large language models to interact with Nextcloud instances through the Model Context Protocol. It supports 30 operations such as notes, calendars, contacts, spreadsheets, and files, and especially provides a revolutionary unified file search function. It supports one - click cloud deployment on Smithery.

The Socket MCP server is a Model Context Protocol service for dependency security scanning, providing security scores and vulnerability detection functions for software package ecosystems such as npm and PyPI, supporting AI assistant integration and multiple deployment methods.

PhonePi MCP is an open - source project that can transform your phone into a toolbox for AI assistants. It enables remote control of phone functions through the Model Context Protocol, including managing contacts, messages, settings, etc. It emphasizes local deployment and network security.

The Arc MCP Server is a Model Context Protocol server that simplifies framework deployment, focusing on shared hosting environments, supporting multi - platform deployment and guided operations.

The YepCode MCP Server is a server implementing the Model Context Protocol. It can transform YepCode processes into AI tools, supports remote and local deployment, and provides functions such as code execution, environment management, and process execution.

A MySQL database operation server based on the Model Context Protocol, providing standardized interfaces for AI models to interact with MySQL, supporting local and remote deployment, and featuring multi - user concurrency and connection pool management.

A customized version of NextChat that creates and deploys MCP servers through chat interactions, integrates LLM models from OpenRouter, and provides functions such as tool extraction, one-click deployment, and AI system integration guides.

The Gemini MCP Server is a middleware designed for the Claude desktop application, enabling image generation through Google's Gemini AI model. This project provides a convenient installation and configuration wizard, supports Docker containerized deployment, and allows users to customize generation parameters.

TeamSpeak MCP is a server control tool based on the Model Context Protocol, specifically designed to allow AI models (such as Claude) to manage TeamSpeak voice servers. It provides 39 functional tools, covering all - around operations such as user management, channel control, and permission configuration. It supports multiple deployment methods (PyPI/Docker/local) to achieve automated TeamSpeak management.

The Kernel MCP Server is an open - source server based on the Model Context Protocol (MCP), providing AI assistants with secure access to Kernel platform tools and browser automation capabilities. It supports cloud application deployment, headless browser control, document search, etc., and uses OAuth 2.0 authentication to ensure security.

A production-ready MCP server template for hosting custom AI tools and prompt templates, supporting remote deployment and local operation, helping developers quickly build AI model interaction tools.

A service that provides a Model Context Protocol (MCP) interface for Prometheus, supporting the execution of PromQL queries, exploration of metric data, and providing authentication and containerized deployment support.

This project is a collection of Model Context Protocol (MCP) servers specifically designed for DevOps tools and platforms. It enables large language models (LLMs) to directly interact with mainstream DevOps systems in a standardized way, achieving automated control of operations such as infrastructure, deployment pipelines, and monitoring.

The Alibaba Cloud Supabase MCP Server project connects Supabase projects with AI assistants through the Model Context Protocol standard, providing tools such as project management and database querying, and supporting the deployment and operation of Supabase services on the Alibaba Cloud platform.

Trellis MCP is an interface service that connects AI assistants with Trellis 3D generation models, supporting rapid generation of 3D assets through natural language and importing them into Blender. This project is based on an open - source model and requires self - deployment of the API backend. It is fast and free, but there are stability risks.

Homelab MCP is a collection of Model Context Protocol servers used to manage and monitor home lab infrastructure through Claude Desktop. It supports multiple services such as Docker, Ollama, Pi-hole, Unifi, and UPS, and offers both unified and independent deployment modes.

MCP Server Magic is a tool that helps users easily generate Model Context Protocol servers. It supports generating servers in TypeScript, Python, and Go languages, provides two modes: direct implementation and proxy, and supports multiple deployment methods and authentication configurations.

The WiseVision ROS2 MCP Server is a Python - based implementation of the ROS2 Model Context Protocol (MCP), providing functions such as ROS2 topic and service management, message subscription and publishing, and data black box access. It supports containerized deployment via Docker.

The Cribl MCP Server is a server based on the Model Context Protocol (MCP) for enabling AI to interact with the Cribl API. It allows AI clients to discover and invoke data operations in Cribl deployments through standardized MCP tools.

MCP Atlassian is an integrated tool that provides Model Context Protocol services for Atlassian products (Confluence and Jira), supporting both cloud and on - premise deployments.

An MCP server that does not require local deployment, specifically designed for handling mathematical calculations. It can provide permanently accurate mathematical calculation capabilities for large language models through simple configuration.

The plugged.in App is a comprehensive web application for managing Model Context Protocol (MCP) servers, providing a unified interface to discover, configure, and use AI tools across multiple MCP servers. It supports multi - workspaces, an interactive testing platform, tool management, resource discovery, etc., can be integrated with various MCP clients, and supports self - hosted deployment.