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MCP server that exercises all features of the MCP protocol, serving as reference implementation.

An open standard protocol that gives AI models a universal way to connect to external tools, data sources, and services, introduced by Anthropic in November 2024 and now governed by the Agentic AI Foundation under the Linux Foundation.

Reference MCP server exercising all features of the MCP protocol. Official reference implementation with 84K stars.

Standard protocol definition for MCP servers featuring three-core architecture, universal compatibility, and standardized interfaces using JSON-RPC 2.0 communication.

Bitcoin Lightning channel factory MCP server with 4 tools for protocol overview, UTXO savings estimator, architecture deep-dives (invalidation trees, timeout trees, MuSig2, watchtowers), and resource links. Based on SuperScalar protocol.

An implementation following the official MCP specification, including proper message framing, transport layer implementation, and complete protocol lifecycle management. Provides a foundation for building federated MCP systems that can scale across multiple servers while maintaining security and standardization requirements.

Protocol implementation of the Model Context Protocol in Go, providing a Go-based SDK for building MCP clients and servers.

An implementation project of a JVM-based MCP (Model Context Protocol) server. The project aims to provide a standardized MCP server implementation for the JVM platform, enabling AI models to better interact with the Java ecosystem.

A .NET implementation of the Model Context Protocol (MCP), providing libraries for building MCP servers and clients in the .NET ecosystem.

An MCP server that provides compatibility between MCP protocol and OpenAI-compatible LLM APIs, enabling broader model support for MCP tool integration.

An MCP Server providing access to AMQP (Advanced Message Queuing Protocol) messaging, enabling MCP-based tools to publish and consume messages via the standard AMQP protocol.