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.

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.

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.

emcee is a tool that provides a Model Context Protocol (MCP) server for any web application with an OpenAPI specification, connecting applications such as Claude Desktop to external tools and data services.

Chroma is an open-source vector database that provides memory support for Python and JavaScript LLM applications, supporting multiple client types and document operations.

This project is a server - side implementation based on the Model Context Protocol (MCP), providing seamless integration with the Milvus vector database and enabling multiple LLM applications such as Claude Desktop and Cursor to access database functions through a standardized protocol.

This project provides a series of Model Context Protocol servers based on Quarkus/Java to extend the capabilities of MCP-enabled LLM applications, including various services such as JDBC database interaction, JVM monitoring, and file system operations.

The Quarkus Model Context Protocol (MCP) Server is an open-source protocol server that supports easy integration of LLM applications with external data sources and tools through declarative and programmatic APIs.

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.

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 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.

This project demonstrates a server example developed based on the MCP Java SDK. It does not require the Spring framework and supports providing data and services for LLM applications through the MCP protocol. It includes examples of interacting with MySQL and operating on the file system.

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 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.

This project is a server based on the Model Context Protocol (MCP), which realizes seamless integration with the Milvus vector database and provides a standardized data access interface for LLM applications. It supports direct invocation of Milvus's search, query, and management functions in applications such as Claude Desktop and Cursor.

The Model Context Protocol (MCP) is a protocol for seamless integration of LLM applications with external data sources. It provides .NET templates to simplify the development process, supports multiple operating modes, and includes a visual debugging tool.

The Eunomia MCP Server is an open - source data governance tool for data policy management in LLM applications, supporting integration with the MCP server.

This is an AWS Amplify Data MCP Server project that allows interaction with the data models of Amplify Gen2 applications through natural language, supports operations such as querying and modifying, and needs to be used with AI assistants like Claude.

This project is an implementation of an MCP server based on OpenSearch, providing semantic memory storage and retrieval functions for LLM applications such as Claude, and supporting the connection of AI tools and data sources through a standard protocol.

The Speckle MCP Server is a bridge connecting the Speckle API and client applications, providing tools for interacting with project, model, and object data.

The MCP Python SDK is a Python development toolkit that implements the Model Context Protocol (MCP), allowing developers to build standardized MCP servers and clients to provide context data, tools, and interaction templates for LLM applications.

Bocha is a search engine designed specifically for AI, providing high-quality search services for nearly tens of billions of web pages and ecological content across the network, supporting structured data in multiple vertical fields such as weather, news, and encyclopedias, and suitable for various AI applications.

A Rust-based MCP CLI server template for implementing standardized connections between LLM applications and external data sources and tools.

An implementation of an Etherscan API client based on Go language, supporting multi - chain blockchain data query services for LLM applications through the Model Context Protocol (MCP).

Adaptive Graph of Thoughts is an intelligent scientific reasoning framework based on the Neo4j graph database, which realizes complex scientific reasoning tasks through graph structure and supports integration with AI applications such as Claude Desktop.

The Scrapeless MCP Server is an open - source protocol project that seamlessly integrates LLM applications with external data sources and tools (such as Google Search) in a standardized way, providing dynamic context retrieval capabilities.

The Browserbase MCP Server is an open - source project based on the Model Context Protocol (MCP), providing cloud browser automation capabilities, supporting web page interaction, data extraction, screenshot taking, and JavaScript execution, etc., to help LLM applications seamlessly integrate with external data sources and tools.

The MCP portal is the official community platform for the Model Context Protocol, providing resources such as documentation, practical guides, server implementations, and tool integrations. It supports AI models to access external tools through the MCP protocol, covering a wide range of scenarios from database connections to multimodal applications.

The Baidu Cloud Vector Database MCP Server is a server that provides access to the functionality of Baidu Cloud Vector Database, supporting cooperation with multiple large language model applications.

An MCP server that provides location data for macOS native applications and enables location acquisition functionality through integration with Claude Desktop.

The RISKEN MCP server is a protocol server that provides RISKEN API integration, supporting automated data acquisition, scanning, and analysis, as well as building AI tool applications.

A Dify endpoint plugin that can convert Dify applications into MCP servers. It should be used in a private network to ensure data security.

This is an example of an MCP server for connecting to Kintone, which supports accessing and updating Kintone data through AI applications such as Claude

The Storacha MCP Storage Server is a decentralized storage solution based on IPFS and CID, providing standardized file storage and retrieval interfaces for AI applications, supporting data sovereignty, verifiability, and cross - system integration.

This project implements a ClickHouse MCP server for seamless integration of the ClickHouse database with AI applications such as large language models (LLMs), supporting functions such as querying databases and obtaining table structures.

The MCP Rust CLI server template is a simple application template that demonstrates how to implement an MCP CLI server in Rust, used to connect LLM applications with external data sources and tools.

This is an unofficial Quickbase JSON RESTful API connector developed based on the Model Context Protocol (MCP). It supports interacting with Quickbase data through natural language and enables management operations of resources such as applications, tables, fields, and records.

This is a list containing a large number of open - source AI projects, covering multiple fields from natural language processing, image generation to automated workflows. These projects aim to help developers build various applications using AI technology, including chatbots, code - generation tools, data - processing systems, etc.