iflow-mcp_johnymontana-neo4j-mcp-ecommerce 0.1.0

MCP server for an ecommerce store backed by Neo4j

Neo4j MCP Ecommerce Server (Python)

An MCP server that exposes two tools backed by Neo4j:

• search_customer(q: str) — search customers by name or email
• recommend_product(customer_id: str, limit: int = 5) — recommend products via co-purchase

This project uses uv for dependency and runtime management and the official Python MCP SDK.

Prerequisites

• Python 3.10+
• uv installed (see docs: https://docs.astral.sh/uv/)
• A running Neo4j database

Setup

cd python
# (optional) create and activate a project venv
uv venv && source .venv/bin/activate

# install dependencies
uv sync

# configure environment
cp env.example .env
# edit .env with your credentials

Required environment variables:

• NEO4J_URI (e.g. bolt://localhost:7687)
• NEO4J_USERNAME
• NEO4J_PASSWORD
• NEO4J_DATABASE (optional; defaults to Neo4j driver default)

Run the MCP server

The server runs with stdio transport (standard for MCP servers):

uv run neo4j-mcp-ecommerce

The server communicates over stdio and can be used with MCP clients like Claude Desktop or the MCP Inspector.

Testing with MCP Inspector

You can test the server using the MCP Inspector, a web-based tool for debugging MCP servers:

1. Run the MCP Inspector:

npx @modelcontextprotocol/inspector

2. In the inspector interface:

   • Click "Add Server"
   • Choose "Command" as the transport
   • Set the command to: uv run neo4j-mcp-ecommerce
   • Set the working directory to: /path/to/your/python/directory
   • Click "Connect"

3. Once connected, you can:

   • View available tools (search_customer and recommend_product)
   • Test tool calls with sample parameters
   • Inspect responses and debug any issues

The inspector provides a convenient way to test your MCP server without needing a full MCP client setup.

Tools

search_customer

• Input: q — substring to match name or email (case-insensitive)
• Output: list of customer maps: { id, nodeId, name, email }

recommend_product

• Input: customer_id — your domain identifier on :Customer {id: ...}
• Input: limit — max recommendations (default 5)
• Output: list of { productId, title, score }

Notes

• Credentials are read from environment variables (dotenv is supported for local dev).
• Cypher assumes labels/properties: :Customer {id, name, email} and :Product {id, title} with relationships approximating PURCHASED/CONTAINS/PRODUCT. Adjust queries to match your schema if different.