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 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.

Browser MCP is an MCP server + Chrome extension that enables browser automation through AI applications (such as VS Code, Claude, etc.). It features fast response, privacy protection, staying logged in, and avoiding detection.

Coco AI is a unified search platform that integrates enterprise applications and data (such as Google Workspace, Dropbox, GitHub, etc.), providing cross-platform search and AI-driven team chat functions, aiming to improve work efficiency and collaboration experience.

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 ClickUp MCP Server is a model context protocol server for integrating ClickUp tasks with AI applications, supporting task, space, list, and folder management through a standardized protocol.

This project provides an MCP server for deploying code to Google Cloud Run services, supporting deployment from various sources such as AI-assisted IDEs, AI assistant applications, and proxy SDKs.

A secure code sandbox environment based on Docker containers, providing an isolated execution space for AI applications.

Obsidian's MCP Tools plugin provides AI applications with the ability to securely access the knowledge base

The GPT Researcher MCP Server is an AI research server based on the MCP protocol. It can provide high-quality and optimized research results for LLM applications through in-depth web search and verification.

The Zen7 Payment Agent is the first practical implementation of a DePA decentralized payment agent. It adopts a multi - agent collaborative architecture, supports the A2A and MCP protocols, and provides multi - chain and multi - currency payment solutions for AI agents and Dapp applications, enabling automated cryptocurrency payments and LLM - driven intent recognition.

Open Data MCP is an open - source project aiming to quickly connect public data sets to LLM applications through the MCP protocol, enabling convenient access to open data and community - based publishing.

Open Data MCP is an open - source project aiming to quickly connect public data sets to LLM applications through the MCP protocol. The project provides a CLI tool to achieve a 2 - minute connection (currently supporting Claude) and establishes a community collaboration framework that allows developers to easily contribute and publish public data sets. The core goal is to build an infrastructure that connects all LLM applications with millions of public data sets.

The ClickUp MCP Server is a model context protocol server for integrating ClickUp tasks with AI applications. It supports managing tasks, spaces, lists, folders, etc. through a standardized protocol and provides functions such as time tracking and tag management.

A secure Docker container code sandbox environment that provides an isolated execution space for AI applications, supporting multiple programming environments and file operations.

This project is an MCP server for deploying code to Google Cloud Run, supporting deployment through AI agents, IDEs, and assistant applications.

This project is an MCP server based on the AviationStack API. It provides query tools for real-time and future flight data, aircraft types, and detailed information, facilitating the integration of aviation data into applications.

Model Context Protocol (MCP) .NET sample library, demonstrating how to use the MCP protocol to standardize the context interaction of large language models (LLMs) in .NET applications. It includes examples such as a YouTube subtitle extractor, supports flexible switching of LLM providers, and enables the construction of AI workflows.

BrowserTools MCP is a powerful browser monitoring and interaction tool that enables AI applications to capture and analyze browser data through Chrome extensions and a local Node server, and is compatible with multiple MCP clients.

MCPHub is an embeddable Model Context Protocol (MCP) solution for AI service integration. It provides a unified way of configuration and management, supports multiple AI frameworks (such as OpenAI Agents, LangChain, Autogen), and simplifies the connection between MCP servers and AI applications.

MoziChem - MCP is a collection of servers for chemical engineering and chemical applications based on the Model Context Protocol (MCP). It provides professional tools such as thermodynamic models, equation of state calculations, and phase equilibrium calculations, and supports AI assistants to perform complex chemical engineering calculations.

The StrawHat AI development repository provides a complete solution for building local and online AI development environments, including various tools such as the Ollama backend, Open - WebUI frontend, and Claude desktop proxy, supporting rapid deployment and development of AI applications.

A high-performance MCP server implemented in Go language, providing AI agents and applications with the ability to query and access the Redfish API through natural language, enabling intelligent management and monitoring of data center infrastructure.

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.

Frida MCP is an MCP protocol implementation based on the Frida dynamic detection toolkit, providing AI systems with the ability to interact with mobile and desktop applications.

The project aims to connect RAG applications to open-webui through the MCP protocol to achieve model context interaction, including basic PoC verification, knowledge base integration, and client docking.

A WeChat official account API integrated service based on the MCP protocol, providing functions such as material management, draft editing, and article publishing for AI applications.

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.

The Pierre Fitness API is a multi-protocol fitness data API that supports securely obtaining fitness data from providers such as Strava and Fitbit. It provides intelligent analysis for AI applications through MCP, A2A, and REST APIs, including enterprise-level API management, real-time analysis, and intelligent analysis of multiple sports types.

The Pega DX MCP Server is an experimental project aiming to transform Pega Infinity™ applications into an intuitive conversational experience through the Model Context Protocol (MCP). It serves as a bridge between the Pega DX API and the natural language interface, enabling GenAI agents, IDEs, and other MCP-supported tools to interact with Pega Infinity™ applications using simple human-readable commands.

React MCP is a server that implements the model context protocol, providing Claude AI with the ability to interact with React applications, supporting project management, file operations, and process control.

Okta MCP Server is a server based on the Model Context Protocol that allows large - language models and AI agents to manage Okta organizations through natural language instructions, supporting management operations such as users, groups, applications, policies, and logs.

FortunaMCP is a high-performance random number generation server based on hardware entropy, providing real and unpredictable random values for AI applications through various statistical distribution models, suitable for simulation and gaming scenarios.

Yingdao RPA MCP Server is an implementation based on the Model Context Protocol (MCP), providing a service for Yingdao AI Power and other MCP Host tools to call RPA capabilities. It supports the local mode and the open API mode, and can query and run RPA applications, upload files, manage jobs, etc.

click-mcp is a Python library that extends Click applications through Model Context Protocol (MCP) support, enabling AI agents to interact with CLI tools.

The Kafka MCP Server is an Apache Kafka Model Context Protocol (MCP) server implemented in Go. Through a standardized interface, it enables LLM models to perform Kafka operations. It provides functions such as producing/consuming messages, managing topics and consumer groups, and monitoring cluster health. It supports multiple security authentication methods and can be integrated with AI applications such as Cursor and Claude.

Chargebee AgentKit is a toolkit for enhancing the integration capabilities of AI applications with Chargebee and simplifying billing and subscription management.

The G2N MCP Google Calendar SSE Server is a server that implements the Model Context Protocol, providing Google Calendar integration functionality through Server-Sent Events and supporting AI models and applications to manage calendar events.

Spring MCP Bridge is an automated tool that can convert REST endpoints of Spring Boot applications into MCP servers, enabling AI assistants to directly interact with APIs. It supports automatic endpoint scanning, model structure preservation, and document annotation extraction without modifying existing code.

MUXI.ai is an open-source framework for multi-AI-agent systems, offering persistent memory, standardized communication protocols, and thought chain tracking. It supports multiple interface integrations and aims to provide a modular and scalable platform for developers to build advanced AI applications.