MCP E-commerce Load Server

What is MCP E-commerce Load Server?

The MCP E-commerce Load Server is an integrated solution for discovering, validating, and registering affiliate stores and their products in an e-commerce system. It uses AI through the CrewAI framework to automate research, validation, and data prioritization processes.

How to use MCP E-commerce Load Server?

Clone the repository, install dependencies with pip install -e ., configure environment variables in .env, then run python main.py. The server supports full pipeline execution or selective modes using flags such as --only-discover (store discovery only) and --only-products (product collection only).

Key features of MCP E-commerce Load Server

• Store discovery using Serper API
• AI‑powered validation via CrewAI
• PostgreSQL/SQLAlchemy for database storage
• Product collection through Serper MCP Server
• Intelligent product prioritization with CrewAI
• Optional human curation via CSV/dashboard interface

Use cases of MCP E-commerce Load Server

• Automatically discover and validate new affiliate stores
• Collect and prioritize products from discovered stores
• Manage the full e‑commerce data pipeline from discovery to database load
• Enable human‑in‑the‑loop curation before final data insertion

FAQ from MCP E-commerce Load Server

What are the runtime requirements?

Python 3.12 or higher, PostgreSQL, and API keys for external services (OpenAI, Serper, etc.).

How can I run only part of the pipeline?

Use the command‑line flags --only-discover for store discovery or --only-products for product collection. Without flags the full pipeline runs.

Is human curation mandatory?

No, it is optional. The system provides a CSV/dashboard interface for manual review before the final database load.

What external APIs does it use?

The server uses the Serper API for store discovery and OpenAI (via CrewAI) for AI‑driven agents.

Does the server support selective pipeline execution?

Yes, you can execute discovery only, product collection only, or the complete pipeline by passing the appropriate flags when running main.py.