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MCP AI Server

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# 🧠 MCP AI Server — Modular Context Protocol for Intelligent Search Welcome to the **MCP AI Server**, a powerful and modular tool that uses **RAG-based retrieval**, **Pinecone vector storage**, and **MCP** (Model Context Protocol) to create intelligent assistants capable of answering domain-specific questions from your own knowledge base. ![MCP + Claude + Pinecone](https://img.shields.io/badge/Built_with-MCP-blueviolet?style=for-the-badge) ![Python](https://img.shields.io/badge/Language-Python%203.10%2B-blue?style=for-the-badge) ![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg?style=for-the-badge) --- ## 🚀 Features ✅ Local MCP server with FastAPI + Claude/ChatGPT integration ✅ Embedding using `intfloat/multilingual-e5-large` (via SentenceTransformer) ✅ Fast vector search with Pinecone ✅ Documented `tools` exposed to clients like **Claude** and **Cursor IDE** ✅ Secure `.env` usage for managing API keys ✅ Clean, extensible architecture --- ## 🔧 Setup Instructions ### 1. Clone the Repo ```bash git clone git@github.com:MeetRathodNitsan/MCP1.git cd MCP1 ``` ### 2. Create a Virtual Environment ```bash python -m venv .venv # Windows .venv\Scripts\activate # macOS/Linux source .venv/bin/activate ``` ### 3. Install Dependencies ```bash pip install -r requirements.txt ``` ### 4. Configure Environment Variables ```bash OPENAI_API_KEY=your-api-key... PINECONE_API_KEY=... PINECONE_ENVIRONMENT=your-env ``` ### 5. How to use it ```bash uv --directory F:/Project run main.py ```

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