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Multi Server Mcp Agent

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Multi-server MCP-based AI agent with LangGraph, supporting tool-augmented reasoning, RAG (ChromaDB + Ollama embeddings), web search (Tavily), market data (Yahoo

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Описание

Multi-server MCP-based AI agent with LangGraph, supporting tool-augmented reasoning, RAG (ChromaDB + Ollama embeddings), web search (Tavily), market data (Yahoo Finance), weather APIs, and a modular multi-server architecture.

README

��# =؀� Multi-Server MCP Agent A production-style Model Context Protocol (MCP) system that demonstrates how to build a modular AI agent capable of orchestrating multiple specialized servers through a single intelligent client. The system integrates tool-based reasoning, RAG, web search, financial data, weather APIs, and mathematical computation under a unified agent powered by LangGraph and Gemini. --- # (' Key Features >��� Multi-Server MCP Architecture >�� LangGraph ReAct Agent with Tool Calling =ج� Persistent Conversation Memory (Checkpointer) =�� Multi-step Tool Chaining �& Streaming Responses <ب� Rich CLI Interface with Tool Tracing --- ## =��� Retrieval-Augmented Generation (RAG) Local document-based knowledge system Built using LangChain + ChromaDB Embeddings powered by Ollama (embeddinggemma) Semantic retrieval over multiple knowledge collections Hybrid ingestion pipeline with crawling + PDF parsing --- ## <�� Web Search Real-time web search using Tavily API Used for up-to-date information retrieval Integrated as MCP tool for dynamic reasoning --- ## =��� Market Data Server Powered by Yahoo Finance (yfinance) Tools: search_symbol get_market_data get_historical_data Supports stock analysis, historical comparisons, and ticker resolution. --- ## <�&� Weather Server * Built with **Open-Meteo API** * Provides: * Current weather * Forecast data * Historical weather analysis --- ## >��� Math Server (Extended Tool Set) A full-featured mathematical computation server supporting: add subtract multiply divide power sqrt factorial Used as a deterministic reasoning tool for arithmetic and symbolic operations. --- # <��� Architecture text +----------------------+ | AI Client (CLI) | | LangGraph + Gemini | +----------+-----------+ | MCP Protocol | ----------------------------------------------------- | | | | | | �% �% �% �% �% �% Math Market Weather Search RAG (Tools) Server Server Server Server Server Each server is fully independent and communicates via the MCP protocol. --- # >��� RAG Pipeline Details The retrieval system is built using: >��� Ollama Embeddings Model: embeddinggemma =��� Vector Database: ChromaDB (persistent storage) =��� Document Sources: PDF files Crawled web documents =� � Retrieval: Semantic similarity search over chunks Multi-collection support --- # >��� Tech Stack Python 3.11+ MCP (Model Context Protocol) LangGraph LangChain Google Gemini Ollama (EmbeddingGemma) ChromaDB Tavily Search API Yahoo Finance Open-Meteo API Rich (CLI UI) --- # =��� Project Structure text multi-server-mcp-agent/ %%% client.py %%% ingest.py %%% crawl.py %%% .env % %%% knowledge_base/ %%% vector_db/ % %%% servers/ % %%% math_server.py % %%% market_server.py % %%% weather_server.py % %%% search_server.py % %%% rag_server.py % %%% utils/ %%% cli.py --- # =؀� Installation bash git clone https://github.com/Hosein541/multi-server-mcp-agent.git cd multi-server-mcp-agent poetry install --- # =�� Environment Variables text GOOGLE_API_KEY=... TAVILY_API_KEY=... --- # �%� Running the Project bash poetry run python client.py --- # =ء� Example Queries text Compare Tesla and Apple stock over the last month. What is the weather in Tokyo tomorrow? Solve factorial of 10. Search latest AI news. Explain Model Context Protocol. Summarize retrieved documents about LangChain. --- # =�.� Future Improvements Multi-agent orchestration layer Tool ranking / reranking (Router model) Distributed MCP servers Dockerized deployment LangSmith observability Web UI (Streamlit / React) Authentication layer for MCP servers --- # >��� What Makes This Project Special This project demonstrates a real-world implementation of: Modular AI systems using MCP Tool-augmented LLM reasoning Retrieval-augmented generation with local embeddings Multi-step agent execution Real-time tool orchestration Production-style AI system design It is not just a demo  it is a blueprint for building scalable AI agent systems.

from github.com/Hosein541/multi-server-mcp-agent

Установка Multi Server Mcp Agent

У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.

▸ github.com/Hosein541/multi-server-mcp-agent

FAQ

Multi Server Mcp Agent MCP бесплатный?

Да, Multi Server Mcp Agent MCP бесплатный — установка в пару кликов через Unyly без оплаты.

Нужен ли API-ключ для Multi Server Mcp Agent?

Нет, Multi Server Mcp Agent работает без API-ключей и переменных окружения.

Multi Server Mcp Agent — hosted или self-hosted?

Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.

Как установить Multi Server Mcp Agent в Claude Desktop, Claude Code или Cursor?

Открой Multi Server Mcp Agent на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.

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