A NestJS module for easily exposing AI tools, resources, and prompts via the Model Context Protocol (MCP), supporting multiple transport types and automatic discovery and registration functions.

The Terrakube MCP Server is a Model Context Protocol server for managing Terrakube operations, providing comprehensive API integration for workspace, variable, module, and organization management.

A set of lightweight programs including weather services and financial analysis modules, providing specific functions through a standardized model context protocol.

MCP Mediator is a Java - based implementation of the Model Context Protocol (MCP) mediator, providing seamless integration between MCP clients and servers, supporting efficient communication and tool execution. The project includes core modules, examples, and various service integrations, supports quickly converting existing code into MCP services through annotations, and has the ability to proxy multiple servers.

This project includes the Cloud Security Alliance Model Context Protocol server, covering various functional modules and service interfaces.

This project integrates Claude AI with Pure Data through the Model Context Protocol, supporting dynamic creation, modification, and control of Pure Data audio processing modules through natural language.

This project includes the Cloud Security Alliance model context protocol servers, covering various functional modules and service interfaces, including multiple useful tools imported from Anthropic and chat services provided by CSA.

This project enables large language models to directly understand and generate audio effect modules in the Max audio processing software through the Model Context Protocol (MCP). It supports explaining, modifying, and creating audio effect modules and provides an interaction interface with LLMs.

The Terrakube MCP Server is a model context protocol server developed based on TypeScript, designed specifically for the Terrakube platform, providing functions such as workspace management, variable handling, module operations, and organization management.

This project provides a series of example modules using the AWS Model Context Protocol (MCP), covering multiple languages and technology stacks, including TypeScript, Python, Spring AI, etc., demonstrating the application of MCP in scenarios such as client-server communication, ECS deployment, and RAG integration.

The Claude-LaTeX MCP integration project connects Claude AI with LaTeX editors through Anthropic's Model Context Protocol (MCP), providing AI - assisted functions for academic writing, science fiction creation, and philosophical writing, including core tools such as formula generation, document structure optimization, and reference management, as well as professional extension modules for different types of content.

The NestJS MCP module is an integration module designed for the NestJS framework to simplify the implementation of the Model Context Protocol (MCP) server. It supports multiple transport layers (including STDIO and HTTP/SSE) through decorators (such as @McpResource, @McpTool, @McpPrompt) and familiar NestJS patterns, enabling developers to quickly build MCP - compatible services.

This project provides a series of Model Context Protocol (MCP) servers for enhancing the external capabilities of AI assistants, including independent implementation modules for specific functions such as educational course queries.

A NestJS module for creating MCP (Model Context Protocol) services that support Server-Sent Events (SSE) transmission, providing functions such as automatic discovery of tools and resources, request validation, and progress notification.

This project is a development environment integrating the ModelContextProtocol (MCP) SDK and servers. It manages the Python and TypeScript SDKs and officially maintained servers through Git sub - modules, aiming to provide basic context and tool support for developing new MCP servers.

The @cmmv/mcp module of CMMV implements the Model Context Protocol (MCP), providing a standardized interface for CMMV applications, supporting the interaction between LLMs and applications, and including functions such as tool registration, validation, and connection management.

This project is a collection of multiple Model Context Protocol (MCP) servers, aiming to provide dedicated interfaces for large language models. These servers are created by non - professional developers with the help of AI tools and currently include two functional modules: Perplexity search integration and keyword analysis.

A NestJS module for easily exposing AI tools, resources, and prompts via the Model Context Protocol (MCP), supporting multiple transport types and dependency injection.