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.

hyper-mcp is a high-performance MCP server based on WebAssembly plugins, supporting plugin distribution through container registries and suitable for various AI application scenarios.

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.

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.

HiveChat is an AI chat application designed for small and medium - sized teams. It supports multiple large - model service providers and provides functions such as group management, Token limits, and third - party login.

Eino is an LLM application development framework designed specifically for Golang, aiming to simplify the AI application development process through concise, scalable, reliable, and efficient component abstraction and orchestration capabilities. It provides a rich component library, powerful graphical orchestration functions, complete stream processing support, and a highly scalable aspect mechanism, covering the full-cycle toolchain from development to deployment.

Desktop Commander MCP is an AI assistant tool that enables the Claude desktop application to execute terminal commands and manage the file system. It supports functions such as code search, editing, process management, and remote file reading.

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.

MCP Link is an automated tool that can convert any API conforming to the OpenAPI V3 specification into an MCP server, enabling existing RESTful APIs to be seamlessly integrated into an AI-driven application ecosystem.

MCP Notes is an intelligent note - taking application based on the MCP protocol, supporting AI - driven note management and web interface operations, and using DynamoDB to store data.

LYRAIOS is a multi-AI agent operating system based on the Model Context Protocol (MCP), aiming to extend AI application functions by connecting financial networks and public blockchain chains, providing services such as blockchain operations, fintech analysis, and educational learning.

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.

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

adb - mcp is a proof - of - concept project aiming to provide an interface for LLMs through the MCP protocol to create an AI agent for controlling Adobe tools (such as Photoshop and Premiere). This project includes the MCP server, Node command proxy server, and Adobe application plugins, supporting natural language instruction operations on Adobe software and suitable for image and video editing automation.

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.

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. 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.

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.

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

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.

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

A desktop application for managing MCP servers, supporting integration with AI tools such as Claude and Cursor, and providing functions such as server import, environment variable configuration, and real - time monitoring.

The Metoro MCP Server is an open-source project that connects Kubernetes cluster data to the Claude desktop application via the Model Context Protocol, enabling AI-driven cluster observation.

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.

This project is a Python server based on the MCP protocol, providing functions for querying and calculating soil and water conservation technical specifications, including engineering calculations such as Manning's coefficient, earth pressure coefficient, drainage ditch flow velocity, and slope stability, as well as the conversion between latitude and longitude and UTM/TWD97 coordinates in Taiwan region. It is suitable for AI application integration.

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.

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.

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.

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.

BurpMCP is a Burp Suite extension that enhances application security testing capabilities by integrating modern AI technology and provides intelligent assisted testing functions.

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.

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.

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.

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.

ToolJet MCP is a bridge connecting AI assistants to the ToolJet platform, enabling programmatic interaction through the Model Context Protocol and supporting functions such as user management, workspace operations, and application management.

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.