eMCP-Nexus

eMCP Nexus is an AI-powered marketplace that hosts MCP tools and exposes them via an API-backed platform. It leverages a semantic search engine (FAISS), an AI-driven recommendation system, and a RAG-powered chatbot to help users discover, test, and deploy MCP tools on demand. Engineers can upload and monetize their MCP tools by connecting their GitHub repos, set per-task pricing, and deploy tools instantly. Users can search in natural language, get personalized suggestions, and execute tasks through simple HTTP calls or the provided API endpoints. The system supports crypto and traditional payments, as well as real-time analytics and monitoring for tool usage.

Prerequisites:

• Python 3.9+
• Docker (for local development or deployment)
• Node.js (for frontend, if applicable)

Step-by-step installation:

1. Clone the repository:

git clone https://github.com/your-org/eMCP-Nexus.git
cd eMCP-Nexus

2. Create a Python virtual environment (optional but recommended) and install backend dependencies:

python -m venv venv
source venv/bin/activate  # on macOS/Linux
# Windows: .\venv\Scripts\activate
pip install -r backend/requirements.txt

3. Start the backend server (development):

uvicorn backend.main:app --reload

4. Open the API docs to explore endpoints:

• Visit http://localhost:8000/docs for interactive Swagger UI.

Optional: Docker Compose (single-command deployment):

docker-compose up --build

Prerequisites for Docker Compose: Docker installed and docker-compose available on your system.

Tips and notes:

• Environment variables: configure payment providers, database URLs, and external service keys via environment variables as needed by your deployment. Example: DB_URL, PAYMENT_PROVIDER, SECRET_KEY, etc.
• If you customize the tool deployment workflow, ensure GitHub integration tokens and webhooks are provisioned securely.
• For production, consider configuring a reverse proxy (e.g., Nginx) and enabling SSL/TLS termination.
• Review the tool reputation and usage analytics to monitor tool quality and trust in the marketplace.
• When using Docker, ensure proper resource limits (CPU/mmemory) to prevent runaway tasks.
• If the API docs are slow to load, consider pre-warming caches or using a dedicated frontend to minimize latency.