Claude-Powered MCP Agent for Smart Supply Chain
This project simulates a smart warehouse system powered by Claude using Model Context Protocol (MCP) patterns. The system manages inventory, automated guided vehicles (AGVs), and order processing through a set of specialized agents coordinated by Claude.
Project Structure
claude-mcp-agent-for-supply-chain/
├── agents/ # MCP agent modules
├── simulation/ # Warehouse simulation logic
├── api/ # FastAPI endpoints
├── logs/ # Action and decision logs
├── claude_interface.py # Interface to Claude API
├── main.py # Main application entry point
Features
- MCP-style Modular Agents: InventoryManager, AGVPlanner, RestockAgent, Coordinator
- Warehouse Simulation: Inventory tracking, AGV movement, order processing
- Claude Integration: Uses Anthropic's Claude API for decision-making
- API Endpoints: FastAPI-based endpoints for interacting with the system
Setup
-
Create a virtual environment:
python -m venv venv -
Activate the virtual environment:
- Windows:
venv\Scripts\activate - Unix/MacOS:
source venv/bin/activate
- Windows:
-
Install dependencies:
pip install -r requirements.txt -
Set up environment variables:
cp claude.env.template claude.envThen edit
claude.envto add your Anthropic API key. -
Run the application:
python main.py
API Endpoints
GET /inventory: Get current inventory statusGET /agvs: Get status of all AGVsPOST /orders: Create a new orderPOST /ask-agent: Send a query to Claude agentGET /logs: Get recent action logs
Example Usage
Example prompt to Claude:
The inventory for Product X is at 5 units, below the threshold of 10. Two AGVs are available. Suggest an optimal action.
Claude will analyze the situation and return structured actions that the system can execute.
License
MIT