A Kubernetes cluster management server based on the MCP protocol, supporting interaction with the Kubernetes cluster through the command line or chat interface, providing functions such as resource management and Helm chart operations.

Open Multi - Agent Canvas is an open - source multi - agent chat interface that supports managing multiple agents in dynamic conversations for travel planning, research, and general task processing.

LLM Context is a tool that helps developers quickly inject code/text project content into the chat interface of large language models, supporting intelligent file selection and multiple integration methods.

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.

A full-stack application that integrates the Model Context Protocol (MCP) with Anthropic's Claude LLM, providing an interactive chat interface and utilizing MCP tools.

mcp - scaffold is a development sandbox for verifying the Model Context Protocol (MCP) server, providing support for local LLMs (such as LLaMA 7B) and cloud inference, including a chat interface and reference architecture.

The Ollama MCP Server is a bridge tool that connects the local large language models of Ollama and the Model Context Protocol (MCP). It provides complete API integration, model management, and execution functions, and supports OpenAI - compatible chat interfaces and visual multimodal models.

The NiFi MCP project provides a chat interface based on natural language interaction, allowing users to interact with Apache NiFi instances through LLM models, supporting querying, documenting, and operating NiFi components.

The MCP Chat Adapter is a server based on the MCP protocol that provides a standardized interface for LLMs to interact with the OpenAI-compatible API. It focuses on chat model scenarios and supports conversation management and persistent storage.

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.

The Optuna MCP Server is a service based on the Model Context Protocol (MCP) that automates the optimization and analysis process using Optuna. It supports various application scenarios, such as automatic hyperparameter optimization for LLMs, interactive analysis of optimization results through a chat interface, and optimization of the input and output of other MCP tools.

This is an MCP protocol demonstration project based on Cloudflare Workers and Remix 3, showing how to embed an interactive calculator widget in the AI chat interface. The project includes a complete MCP server implementation, state management, and widget communication system, and a hidden Easter egg in the TRON style is specially designed.

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

WhatsApp Web MCP is a Node.js application that connects WhatsApp Web with AI models through the Model Context Protocol (MCP), providing a standardized interface for automated messaging, contact management, and group chat functions.

The Perplexity AI MCP Server project provides a standardized interface to access the features of Perplexity AI, including chatting, searching, and document retrieval.

Perplexity MCP Server is a Python-based interface service that provides tools for interacting with the Perplexity API, supporting query responses, maintaining chat history, and managing conversations. It configures models through environment variables and stores chat data locally, making it suitable for integration in development environments.

OmniLLM is an MCP server that serves as a bridge between Claude and other large language models (such as ChatGPT, Azure OpenAI, and Google Gemini), providing a unified AI access interface.

The EspoCRM MCP Server is a comprehensive model context protocol server that provides seamless integration with EspoCRM, supporting 47 tools for complete CRM operations, including contact, account, opportunity, meeting, user, task, lead management, and advanced functions such as team, role, and entity relationship management, along with an AI chatbot interface.

A lightweight client application based on the local OLLAMA model, integrating multiple MCP proxy tools through the BeeAI framework, providing a chat interface and database operation functions.

The Georgia Institute of Technology integrated MCP server provides a comprehensive interface for LLM to access the GT academic research ecosystem, integrating the functions of multiple systems such as course systems, research resources, and campus facilities. It newly adds ChatGPT HTTP API integration and fixes the 500 error of the OSCAR system.

An MCP server implemented for the OpenAI API, providing a standardized interface to connect Augment with OpenAI language models, supporting functions such as chat completion, model listing, and embedding generation.

An interactive chat interface project for querying Neo4j databases through natural language, integrating Chainlit, Neo4j MCP, and Claude LLM technologies.

This project implements a Langchain - based chatbot system by building multiple MCP servers (mathematical calculation, weather query, LLM selection) and a client. Users can interact with the robot through the Streamlit interface.

The MCP server provides infrastructure connection services for LLM agents, supporting interaction with databases, file storage, Kafka, and web interfaces. It is deployed in a containerized manner and integrated with Gitlab Agent and LLM Chat to achieve automated data pipeline creation

The Perplexity MCP Server is a Python-based interface tool that provides functions to interact with the Perplexity API, supporting query responses, maintaining chat history, and managing conversations. You can configure the model through environment variables, and it has features such as local storage of chat data, streaming responses, and a Web UI.

The Perplexity AI MCP Server project provides standardized interfaces to access the functions of Perplexity AI, including chatting, searching, and document retrieval.

A simple Python client for connecting to the arXiv MCP server for paper search, using the Groq language model to process queries and providing a chat interaction interface.

The Perplexity MCP Server is a Node.js - based server that implements Anthropic's Model Context Protocol (MCP) to connect Claude with Perplexity's language models and provides enhanced AI interaction tools. It supports two main tools: advanced chat completion and a simplified single - query interface.

This project uses the Waku framework and React server components to demonstrate how to connect to the Anthropic API through Neon's MCP server to implement a custom chat interface.

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.

This project is a Python chatbot server based on IBM Watsonx.ai and the MCP protocol. It provides medical consultation functions, supports building a Web interface through Flask, and realizes symptom diagnosis and personalized greetings.

A powerful multi - source deal aggregation MCP client that integrates Slickdeals, RapidAPI, and web scraping functions, providing an interactive chat interface and intelligent deal filtering and comparison functions.

Forgejo MCP Server is an integration plugin that connects Forgejo with the MCP system, supporting command execution and repository management through the chat interface.

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.

An experimental Kubernetes MCP server that exposes Kubernetes functionality to AI chat interfaces via kubectl, enabling AI assistants to help analyze and manage cluster resources.

mcp-scaffold is a sandbox environment for verifying the Model Context Protocol (MCP) server, supporting local and cloud LLM inference, providing a chat interface and reference architecture.

A Telegram server implementation based on the MCP architecture, providing API interfaces for functions such as message search, sending, and chat management

An MCP client application based on Streamlit, supporting connection to multiple LLM providers (such as OpenAI, Anthropic, etc.) and interaction with MCP servers, providing tool testing and chat interface functions.

A TypeScript project integrating Langchain and MCP tools, supporting interaction with language models through a chat interface and execution of various tools.

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