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.

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.

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.

A reference project implementing the Model Context Protocol (MCP), providing a standard for tool calls between LLMs and applications, including local and remote call implementations, and integrating AWS Bedrock and Claude 3.7.

A server implementation based on the Model Context Protocol (MCP) for executing CMD commands and SSH connections on Windows and Linux systems, supporting the integration of command - line operations through MCP - compatible applications.

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.

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).

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 privateGPT MCP Server is a server implementation based on the Model Context Protocol (MCP), allowing users to integrate privateGPT as an agent with MCP clients, providing a secure and modular AI application development environment.

An MCP server implementation designed for the Claude desktop application, providing persistent memory functions for large language models, including a tiered memory architecture, multiple memory types, and semantic search features.

A minimal server/client application implementation based on the Model Context Protocol (MCP) and Azure OpenAI, including the FastMCP server, Playwright testing framework, and MCP-LLM Bridge conversion function.

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.

Neo N3 Model Context Protocol (MCP) is a standardized interface protocol for the interaction between AI agents and applications and the Neo N3 blockchain. It provides an easy - to - use server implementation, supports direct running via npx, and does not require manual environment configuration. The protocol includes functions such as blockchain information query, wallet management, asset transfer, and smart contract interaction, and additionally provides an HTTP server to expose functions in the form of RESTful APIs.

This project includes multiple MCP server and client implementations based on Python 3.11, involving simple applications of the Langgraph framework, multi-server collaboration, and the development of a ChatGPT clone project.

MCP4Go is a Model Context Protocol (MCP) library implemented in Go language, aiming to simplify the development of AI applications and provide a complete protocol implementation and high-level abstraction.

Implementation of the Modal MCP Server for interacting with Modal volumes and deploying Modal applications in Cursor

MCP Server is an implementation of the Model Context Protocol based on FastAPI, providing a standardized interface between LLM models and applications, and supporting multiple tools and real-time interaction.

An MCP server implementation designed for the Claude desktop application, providing persistent memory functions, including a tiered memory architecture, multiple memory types, and semantic search features.

An implementation of the MCP server based on iFlytek, supporting intelligent workflow scheduling and multi - model hybrid application architecture.

An MCP service implementation that connects LLM applications with the Unleash feature flag system