AI 机器学习 资源

This document provides a summary of the client.py and server.py files from this repo.

TweetFlow AI Agent is an AI-powered application that generates and posts tweets on behalf of the user using Google's Gemini Large Language Model (LLM). The agent is deployed on an MCP (Multi-Agent Communication Protocol) server and responds to user instructions to create and publish context-aware tweets in real time.

The OpenFinance MCP Server is a Go-based application that connects to the Brazilian Open Finance ecosystem through Pluggy.ai, providing secure and structured access to financial data such as account balances, transactions, and investments. It is designed to expose these resources to Large Language Models (LLMs) and other AI agents via the Model Context Protocol (MCP), facilitating the development of intelligent financial applications.

This project implements a Model Context Protocol (MCP) server with a Chainlit UI and FastAPI backend that supports agent registration. It allows various tools, resources, and prompt templates to be registered and used by agents.

This repo provides a remote Model Context Protocol (MCP) server without authentication, deployed on app.contextum.org platform.

A Model Context Protocol (MCP) server that provides AI assistants with structured access to your Logseq knowledge graph.

A Model Context Protocol (MCP) server for Mem0, providing memory capabilities to LLMs through the MCP protocol.

GemForge-Gemini-Tools-MCP: Enterprise-grade Gemini integration for your favorite MCP agents. Supercharge Claude, Roo Code, and Windsurf with codebase analysis, live search, text/PDF/image processing, and more.

A production-ready MCP (Model Context Protocol) server running in a Kali Linux Docker container, providing AI assistants with access to a comprehensive security toolset.

A Model Context Protocol (MCP) server that provides access to the Metropolitan Museum of Art Collection through natural language interactions. This server allows AI models to search The Met's art collection and have art works available as a Resource.

A ready-to-use implementation of the Model Context Protocol (MCP) server that integrates with Claude AI models.

Query models hosted on Groq for lightning-fast inference directly from Claude and other MCP clients through the Model Context Protocol (MCP).

A Model Context Protocol (MCP) server that enables AI assistants like Large Languange Model (LLM) to interact with Amazon's Data Kiosk API for analyzing seller and vendor data.

A Model Context Protocol (MCP) server for integrating VISO TRUST API capabilities with AI assistants.

Combinations of MCP servers I find useful.

MCP Go- Cursor.ai AI-.

Shinkai is a two click install AI manager (Local and Remote) that allows you to create AI agents in 5 minutes or less using a simple UI. Agents and tools are exposed as an MCP Server. There is a companion repo called Shinkai Node, that allows you to set up the node anywhere as the central unit of the Shinkai Network, handling tasks such as agent management, job processing, and secure communications. You can find it here.

A Model Context Protocol server that provides Text-to-Speech (TTS) capabilities using Kokoro and Speech-to-Text (STT) capabilities using NVIDIA NeMo Parakeet models, enabling interactive voice dialogues.

This project is a fork of steipete/claude-code-mcp with enhanced orchestration capabilities, reliability improvements, and additional documentation.

This repository implements an MCP-compatible research assistant chatbot system. It consists of:

A powerful conversational agent with retrieval-augmented generation, MCP server, long- and short-term memory, and tool integrationspowered by LangGraph, LangChain, Redis, PostgreSQL, and Pinecone.

omni ai mcp server dev desktop app

This project is based on the code from the Deeplearning training class: MCP: Build Rich-Context AI Apps with Anthropic.

This repository contains a collection of Model Composition Platform (MCP) servers and services designed to facilitate the integration and deployment of various AI/ML models and services.

This MCP Server is a solution designed to enable AI LLMs and AI agent applications (e.g. claude desktop) to interact with the Australian Business Number (ABN) Lookup Web Services API .

A Model Context Protocol (MCP) server implementation that integrates with the Nutrient Document Web Service (DWS) Processor API, providing powerful PDF processing capabilities for AI assistants.

An MCP (Model Context Protocol) server for interacting with Android devices through ADB. This TypeScript-based tool provides a bridge between AI models and Android device functionality.

A Model Context Protocol (MCP) server that allows Claude and other MCP-compatible LLMs to interact with and control Elektron synthesizers via MIDI.

This project demonstrates how to build a chat-enabled medical research agent using:

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Middle layer that exposes a ModelContextProtocol (MCP) interface to network devices so any compliant LLM can run readonly CLI commands (via Netmiko) and receive structured JSON (via pyATS Genie) for troubleshooting.

Tired of repeating yourself to Claude every time you start a new chat? myAI Memory Sync is a game-changing MCP tool that seamlessly synchronizes your preferences, personal details, and code standards across ALL your Claude interfaces! Just update once, and your changes instantly appear everywhere - from Claude Desktop to Claude Code, Windsurf, and Claude.ai web. With our cutting-edge caching system, memory-related queries are up to 2000x faster! Stop wasting tokens on repetitive instructions and enjoy a truly personalized AI experience.

A Model Context Protocol (MCP) server that provides real-time graphics card listings from Bazos.cz marketplace. This server enables AI assistants to search and retrieve current graphics card listings through a standardized interface.

RhinoMCP connects Rhino3D to Claude AI via the Model Context Protocol (MCP), enabling Claude to directly interact with and control Rhino3D for AI-assisted 3D modeling, analysis, and design workflows.

Bringing AI practically to science!

An MCP server for scRNA-Seq analysis software Scanpy with natural language!

This project provides an compute poor, locally-executable MCP server that enables protocol-based communication (MQTT, OPC UA, Modbus) and a locally running LLM using Hugging Face transformers.

A translation server based on MCP architecture, supporting multi-language translation and text-to-speech functionality.

S dng MCP Server & Agent LangChain/LangGraph

This project is a fully MCP-compatible VSCode AI workflow server, supporting agile team multi-role collaboration (BA, TL, DEV, QA).

This library provides a lightweight wrapper that makes Anthropic Model Context Protocol (MCP) tools compatible with LangChain and LangGraph.

HoudiniMCP allows you to control SideFX Houdini from Claude Desktop or Cursor using the Model Context Protocol (MCP). It consists of:

This application is a command-line weather service that leverages the Model Context Protocol (MCP) framework to create a sophisticated architecture with client-server interaction enhanced by AI capabilities. The app allows users to query weather information for cities, with LLM-powered spelling correction and natural language processing.

This project is a FastAPI-based application acting as a central client and orchestrator for multiple MCP (Meta Call Protocol) compliant tool servers. It connects to these tool servers via SSE (Server-Sent Events), aggregates their available tools, and leverages a large language model (LLM) to understand user queries and intelligently invoke the appropriate tools. It also includes health checks and an automatic reconnection mechanism to enhance system robustness.

mcp-flowise is a Python package implementing a Model Context Protocol (MCP) server that integrates with the Flowise API. It provides a standardized and flexible way to list chatflows, create predictions, and dynamically register tools for Flowise chatflows or assistants.

A seamless integration between Prism and Model Context Protocol (MCP) servers that empowers your AI applications with powerful, external tool capabilities.

A powerful LinkedIn profile analyzer MCP (Machine Control Protocol) server that interacts with LinkedIn's API to fetch, analyze, and manage LinkedIn posts data. This MCP is specifically designed to work with Claude AI.

An MCP (Model Context Protocol) server and client using FastMCP and LangChain.

A conversational AI agent and voice assistant application built with the LiveKit Agents framework, capable of using Model Context Protocol (MCP) tools to interact with external services for SRE and Kubernetes operations.

A framework for creating multi-agent systems using the MCP (Model Context Protocol) for coordinated, efficient AI collaboration.

An AI Agent that helps you organize your study schedule, LeetCode practice, and daily habits built with Python, MCP, and Starlette.

Connect this Model Context Protocol server to your LLM to interact with Todoist.

This project implements a multi-agent solution using CrewAI and exposes it through FastAPI-MCP server.

Vibe Coder is an MCP (Model Context Protocol) server designed to supercharge your AI assistant (like Cursor, Cline AI, or Claude Desktop) with powerful tools for software development. It helps with research, planning, generating requirements, creating starter projects, and more!

Model Context Protocol (MCP) is an open protocol that enables seamless integration between LLM applications and external data sources and tools. Whether you're building an AI-powered IDE, enhancing a chat interface, or creating custom AI workflows, MCP provides a standardized way to connect LLMs with the context they need. Think of MCP like a USB-C port for AI applications. Just as USB-C provides a standardized way to connect your devices to various peripherals and accessories, MCP provides a standardized way to connect AI models to different data sources and tools.