MCP 服务器

E-commerce MCP Server

A Model Context Protocol server that provides real-time access to MongoDB product data, enabling sophisticated e-commerce queries with price range filters, category searching, and product recommendations through a conversational interface.

README

E-commerce Chatbot with MCP Server (Model Context Protocol)

This project refactors your existing LangChain + FAISS vector database e-commerce chatbot to use MCP (Model Context Protocol) server for real-time product data access.

Key Changes

Removed:

FAISS vector database and embeddings
Static JSON file loading
Vector similarity search

Added:

MCP Server for MongoDB integration
Real-time product queries
Structured database operations
MongoDB text search indexing

Features

Real-time Data: Always up-to-date product information
Structured Queries: Price range, category filtering
Product Recommendations: Based on category and price similarity
Text Input: Supports text queries
Session Management: Maintains conversation context
Coreference Resolution: Handles pronouns and references

Setup

Install dependencies:

pip install -r requirements.txt

Set up environment variables in .env
Start MongoDB:

docker-compose up mongodb -d

Run the application:

uvicorn main:app --reload

API Endpoints

POST /api/v1/chat/ - Text-based chat

Benefits of MCP Integration

Real-time Inventory: Always current stock levels
Complex Queries: Price ranges, category filters
Better Performance: Optimized database queries
Scalability: Direct MongoDB connection
Flexibility: Easy to extend with new query types

The MCP server provides a clean abstraction layer between your LLM and database, enabling more sophisticated product queries while maintaining the conversational interface your users expect.