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.

Notebook Intelligence (NBI) is an AI coding assistant and extensible AI framework designed for JupyterLab. It supports models from GitHub Copilot and other LLM providers, including local Ollama models. It significantly enhances productivity through features such as code generation, auto - completion, and chat interfaces, and supports the integration of Model Context Protocol (MCP) services.

The Image Gen MCP Server is a general AI image generation service that provides cross - platform and multi - model image generation capabilities for various LLM chatbots through the Model Context Protocol (MCP) standard protocol. It supports multiple image models from OpenAI and Google, enabling seamless conversion from text conversations to visual content.

Octagon Deep Research MCP provides AI-driven in-depth research and analysis services, integrates advanced research agents, has no rate limit, is faster than ChatGPT in-depth research, and is more comprehensive than Grok DeepSearch or Perplexity. It supports various MCP clients and is suitable for comprehensive research on any topic or industry.

ChatPPT is an AI - driven presentation generation service that supports generating PPTs according to themes or requirements, automatically creating PPTs by uploading documents, and provides online editing and download functions. Its MCP server supports 18 intelligent document processing APIs, covering various scenarios such as PPT production and resume analysis.

A WordPress Trac data MCP service developed in TypeScript, deployed on Cloudflare Workers, providing AI assistants with comprehensive access to WordPress development data and supporting standard MCP clients and ChatGPT Deep Research functions.

A server that provides model context protocol services for Dify AI, supporting chat completion functions and a restaurant recommendation tool.

The Chatwork MCP Server is a protocol service for operating Chatwork via AI, supporting configuration and use in tools such as Claude Desktop.

The ChatterBox MCP Server is a model context protocol service that enables AI assistants to join online meetings (Zoom, Google Meet, Teams), capture meeting transcripts and recordings, and generate meeting summaries.

This project showcases an MCP service architecture based on Node.js, including backend API services, an MCP server, and a client-side AI chatbot. The MCP server standardizes the API access method, and the client implements the custom data storage function by integrating MCP capabilities.

MCP is an AI chat system based on a client - server architecture that can connect multiple dedicated servers (file system, Slack, Brave search), intelligently analyze user queries, and automatically select appropriate data sources to provide services.

This project is a simplified implementation based on the MemGPT research paper, built using Spring Boot and Spring AI, providing two integration methods: REST services and MCP servers, and including core agent functions and chatbot applications.

MCP Conceal is a proxy service that performs pseudo-anonymization of personally identifiable information (PII) before sending data to external AI providers (such as Claude, ChatGPT, or Gemini) to protect sensitive information. It detects PII and replaces it with fictional but structurally similar fake data using a consistent mapping relationship, thereby maintaining the semantic relationships and structure of the data while protecting privacy.

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.

AI Toybox is a generative AI experimental platform focused on rapid prototyping and testing of MCP tools and agent workflows, providing a chat application and modular MCP service templates.

An MCP server implementation based on the Gemini Flash 1.5 API. It coordinates multiple modular AI services (chatting, searching, RAG, deep reasoning, etc.) through a central router to achieve intelligent request distribution and response integration.

This project is an MCP server implementation based on the Gemini Flash 1.5 API. It coordinates multiple modular AI services (such as chatting, searching, RAG, in - depth reasoning, etc.) through a central router to achieve intelligent request distribution and response processing.

A restaurant reservation system based on Spring Boot and Spring AI, developed using an API-first approach, integrating client code generated by OpenAPI and AI chatbot functionality, and supporting multiple LLM service providers.

Overview: The README.md file provides an overview of the Model Context Protocol (MCP) Server, detailing its components and functions. It explains how MCP enables AI automation through a standardized protocol and connects hosts, clients, servers, local data sources, and remote services. The document also describes the evolution from basic AI chats to advanced AI agents capable of performing automated tasks.