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.

An MCP server project that supports interaction between AI assistants and the macOS version of the ChatGPT desktop application, enabling cross - application command sending and response retrieval.

This project implements an MCP server for interacting with the Wolfram Alpha API, enabling chat applications to perform calculation queries and obtain structured knowledge. It includes an MCP client example based on Gemini, demonstrating how to connect a large - language model to the MCP server for real - time interaction with the Wolfram Alpha knowledge engine.

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.

A sample chat application demonstrating integration with the Model Context Protocol (MCP) server

WebScout MCP is a web application reverse-engineering tool based on the Model Context Protocol, focusing on automated analysis of chat interfaces and streaming APIs, providing browser automation, network traffic capture, and intelligent pattern detection capabilities

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.

Tome is a MacOS application (support for Windows and Linux is coming soon) developed by the Runebook team. It aims to simplify the use of local large language models (LLMs) with MCP servers. By integrating Ollama and managing MCP servers, users can quickly start chatting with MCP-powered models without dealing with complex configurations.

An MCP server designed for ChatGPT's memory function, supporting memory data sharing with other models. Requires environment configuration and application linking for use.

This project tests the capabilities of LLM in information retrieval, API integration (such as IGN's APICARTO and GéoPlateforme services), and code generation through ChatGPT, including functions such as geocoding and postal code query, and explores the application of AI in technical evaluation and development assistance.

A simple client and server example project using Connect API, supporting automatic generation of API tools through Swagger files and integration with Chatlas, including local server operation and Shiny application demonstration functions.

A complete MCP server application based on Windows Forms, integrating LLM API calls, a modern chat interface, tool management, and a configuration system. It can serve as a reference for enterprise-level desktop program development.

Tiny Chat is a chat application developed in Python. It supports installation in development mode and packaged installation, provides a Web interface and database functions, and integrates the MCP service and the RAG service of the OpenAI API.

A guide to the MCP server coding demo, providing a complete process from cloning the repository to configuring the API and building tests, helping developers quickly set up MCP services and integrate them with chat applications.

An MCP Server integrated with New Relic change tracking that records changes such as application deployments through a chat interface.

The DeepSeek MCP Server is an intermediate service used to connect the DeepSeek API with MCP-compatible applications (such as Claude Desktop), supporting various model parameter configurations and chat functions.

The Chatvolt MCP Server is a TypeScript-based application designed to extend the capabilities of AI agents by providing a set of tools to enable them to interact with the Chatvolt platform. This project serves as a bridge between AI models and the Chatvolt API, supporting operations such as managing agents, querying data storage, and handling CRM scenarios, thereby automating complex workflows and providing a natural language interface for the Chatvolt platform.

A full-stack web application based on FastAPI that provides a dual AI assistant experience (chatbot and tool-based agent), supports user authentication, real-time chat, history records, and file analysis, and can be deployed on Heroku.

This project provides code examples for developing and running an MCP server on Oracle OCI, including Python development, AI agent integration, semantic search, SelectAI integration, and connection with AI assistants such as ChatGPT, to help build enterprise - level AI applications.

This project is a Python - based custom MCP (Model Context Protocol) server demonstration, showing how to implement structured communication between clients and servers through a custom protocol. It is suitable for building flexible network applications such as chat rooms or multiplayer games.

A tool for interaction between Claude and the ChatGPT desktop application