Model-Context-Protocol
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This project implements an MCP Server for file system interaction via HTTP requests, supporting file operations and integration with Google Gemini API.
🚀 MCP File System API
📌 Overview
This project implements an MCP (Model Context Protocol) Server that allows interaction with a file system via HTTP requests. It supports file creation, reading, copying, moving, and deletion using FastAPI. Additionally, it integrates with Google Gemini API to process and summarize file contents.
📂 Features
✅ Read various file formats (.txt, .csv, .json, .xml, .docx)
✅ Stream large files efficiently
✅ Integrate with Google Gemini API for text summarization
✅ Cloud Run deployment support
🛠️ Tech Stack
- Python 3.9+
- FastAPI
- MCP (Model Context Protocol)
- Google Gemini API
- Uvicorn (ASGI Server)
- httpx (Async HTTP requests)
- aiofiles (Async File Handling)
- Docker & Cloud Run
🚀 Getting Started
1️⃣ Clone the Repository
$ git clone https://github.com/Vijayk-213/Model-Context-Protocol.git
$ cd Model-Context-Protocol
2️⃣ Set Up a Virtual Environment
$ python3 -m venv venv
$ source venv/bin/activate # On Windows use `venv\Scripts\activate`
3️⃣ Install Dependencies
$ pip install -r requirements.txt
4️⃣ Set Environment Variables
Create a .env file and add your Google Gemini API Key:
MCP_SERVER_URL=http://127.0.0.1:8000
GEMINI_API_KEY=your_gemini_api_key
🔄 Running the Application
Start the MCP Server
$ uvicorn mcp_server:app --host 127.0.0.1 --port 8000 --reload
Run the Main Application
$ python main.py
📌 API Endpoints
| Method | Endpoint | Description |
|---|---|---|
GET | /read-text-from-file?file_path=path.txt | Read file contents |
POST | /invoke | Call MCP function |
🛠️ Future Enhancements
✅ Implement WebSockets for real-time file updates
✅ Add support for cloud storage (Google Cloud Storage, AWS S3)
✅ Improve error handling & logging
📌 Contributing
Feel free to open issues or pull requests to improve the project!
🚀 Happy Coding! 🎯
