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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

Related MCP server: ConnectWise Manage MCP Server

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

  1. Create a virtual environment:

    python -m venv venv
  2. Activate the virtual environment:

    • Windows: venv\Scripts\activate

    • Unix/MacOS: source venv/bin/activate

  3. Install dependencies:

    pip install -r requirements.txt
  4. Set up environment variables:

    cp claude.env.template claude.env

    Then edit claude.env to add your Anthropic API key.

  5. Run the application:

    python main.py

API Endpoints

  • GET /inventory: Get current inventory status

  • GET /agvs: Get status of all AGVs

  • POST /orders: Create a new order

  • POST /ask-agent: Send a query to Claude agent

  • GET /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

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security - not tested
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license - not found
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quality - not tested

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