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Custom MCP Server for Cursor

by Feustey
GitHub
Python
1
  • Apple
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MCP - Question-Answer System with RAG

MCP is an advanced question-answering system using the Retrieval-Augmented Generation (RAG) technique to provide accurate and contextual answers based on a corpus of documents.

Features

  • 🔍 Semantic search in documents
  • 💾 Smart caching with Redis
  • 📊 Persistent storage with MongoDB
  • 🤖 Integration with OpenAI for embeddings and text generation
  • 📈 System monitoring and metrics
  • 🔄 Asynchronous operations management

Prerequisites

  • Python 3.9+
  • MongoDB Community Edition
  • Redis
  • OpenAI API Key

Facility

  1. Clone the repository:
git clone https://github.com/votre-username/mcp.git cd mcp
  1. Install system dependencies:
# MongoDB brew tap mongodb/brew brew install mongodb-community brew services start mongodb-community # Redis brew install redis brew services start redis
  1. Configure the Python environment:
python -m venv .venv source .venv/bin/activate # Sur Unix/macOS pip install -r requirements.txt
  1. Configure environment variables:
cp .env.example .env # Éditer .env avec vos configurations

Quick use

from src.rag import RAGWorkflow # Initialisation rag = RAGWorkflow() # Ingestion de documents await rag.ingest_documents("chemin/vers/documents") # Interrogation response = await rag.query("Votre question ici ?")

Documentation

Tests

python -m pytest tests/ -v

Project structure

mcp/ ├── src/ │ ├── __init__.py │ ├── rag.py # Workflow RAG principal │ ├── models.py # Modèles de données │ ├── mongo_operations.py # Opérations MongoDB │ ├── redis_operations.py # Opérations Redis │ └── database.py # Configuration de la base de données ├── tests/ │ ├── __init__.py │ ├── test_mcp.py │ └── test_mongo_integration.py ├── prompts/ │ ├── system_prompt.txt │ ├── query_prompt.txt │ └── response_prompt.txt ├── docs/ │ ├── installation.md │ ├── usage.md │ ├── architecture.md │ └── api.md ├── requirements.txt ├── .env.example └── README.md

Contribution

  1. Fork the project
  2. Create a branch for your feature ( git checkout -b feature/AmazingFeature )
  3. Commit your changes ( git commit -m 'Add some AmazingFeature' )
  4. Push to branch ( git push origin feature/AmazingFeature )
  5. Open a Pull Request

License

This project is licensed under the MIT License. See the LICENSE file for details.

Contact

Your Name - @your_twitter

Project link: https://github.com/your-username/mcp

This server cannot be installed

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security - not tested
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license - not found
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quality - not tested

How are these scores calculated?

remote-capable server

The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.

Connects to Cursor and enables deep web searches via Linkup and RAG capabilities using LlamaIndex.

  1. Features
    1. Prerequisites
      1. Facility
        1. Quick use
          1. Documentation
            1. Tests
              1. Project structure
                1. Contribution
                  1. License
                    1. Contact

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