vega-janitha/LoRa-wms-mcp-server

LoRa WMS MCP Server

This project provides an AI agent server for interacting with a LoRa-based Water Management System (WMS) via the MCP framework. It exposes tools for retrieving node and tank data, as well as controlling relays on WMS nodes.

Features

• Retrieve node details from a WMS gateway
• Get tank levels for nodes
• Control relay states on nodes
• FastAPI-based server via MCP

Project Structure

• : Entry point. Defines MCP tools and runs the server.
• : Handles HTTP requests to the WMS backend API.
• : Utility functions, including API header generation.
• : Loads configuration and secrets from environment variables.
• : Python dependencies.

Setup

1. Clone the repository

2. Install dependencies

   pip install -r requirements.txt
   

3. Configure environment variables

   Create a .env file in the root directory with:

   LIA_API_SECRET=your_lia_api_secret
   

   The default API host is set to https://neuraedgeai.com/backend in .

4. Run the server

   python main.py
   

Usage

The server exposes the following tools:

• get_node_details(gateway_id, node_id=None):
  Get details for a node or all nodes on a gateway.

• get_tank_details(gateway_id, node_id=None, tank_number=None):
  Get tank levels for a node or all nodes.

• control_node_relay(gateway_id, node_id, relay_number, relay_state):
  Control the relay state (0/1) on a node.

See for tool signatures and error handling.

Development

• Python 3.10+
• Uses mcp-python, FastAPI, and Uvicorn.

License

See LICENSE (not included by default).

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Note:
API credentials and endpoints are required for the server to function. Ensure you have access to the WMS backend.