ESP32 MCP Server — Connect LLMs with IoT Devices

A lightweight Model Context Protocol (MCP) bridge that lets large language models (LLMs) directly communicate with an ESP32 running Tasmota or similar firmware.

This project demonstrates how an AI assistant (like ChatGPT or Copilot) can reason about user intent and execute physical actions — such as toggling relays or reading sensors — in real time, using standard HTTP commands.

📖 Overview

Traditional IoT automation relies on fixed rules, MQTT topics, or REST endpoints.
This project replaces all that with a simple concept:

The LLM talks to your ESP32 through a universal protocol — MCP.

No firmware rebuilds, no MQTT brokers, no cloud dependencies.
Just plain human language turned into structured, executable commands.

You can read the full article here:
👉 Connecting LLMs and IoT: How an ESP32 Can Speak MCP and Follow AI Commands

And watch the walkthrough video:
🎥 ESP32 + MCP + LLM Integration Demo

🧠 What It Does

• Bridges MCP (Model Context Protocol) and your ESP32 firmware (e.g., Tasmota)

• Exposes a single tool: tasmota-cmd, letting LLMs send commands like:

  /tasmota-cmd {"command": "Power1 1"}

• Works locally — no API keys or external services required

• Compatible with Visual Studio Code Copilot Chat or any LLM supporting MCP

⚙️ How It Works

LLM (Copilot/ChatGPT)
        ↓
     MCP Protocol
        ↓
 Node.js MCP Server
        ↓
  ESP32 (Tasmota)

The MCP server receives structured requests, converts them into Tasmota commands (e.g. Power1 ON, Backlog PulseTime1 400; Power1 1), and sends them via HTTP to your ESP32 device.
The responses are returned to the model as plain text for reasoning and follow-up actions.

🚀 Quick Start

1. Clone this repo

git clone https://github.com/<your-username>/esp32-mcp-server.git
cd esp32-mcp-server

2. Install dependencies

npm install

3. Configure your device IP

Edit the constant inside index.js:

const DEVICE_IP = "192.168.1.xxx";

4. Run the server

node index.js

You’ll see output similar to:

MCP HTTP server:  http://localhost:3000/mcp
Health:           http://localhost:3000/health
Debug:            http://localhost:3000/debug?command=Power1%201

💬 MCP Server in VS Code

To connect with GitHub Copilot Chat or compatible tools, add this configuration in your .config/github-copilot/ file:

{
  "servers": {
    "esp32-mcp": {
      "url": "http://localhost:3000/mcp",
      "type": "http"
    }
  }
}

Reload Copilot, and you’ll see your new MCP tool:

/tasmota-cmd {"command": "Power1 1"}

🧩 Dependencies

• Node.js 18+

• @modelcontextprotocol/sdk

• express

• zod

🧰 Compatible Firmwares

📺 Reference & Resources

• 📰 Full Article on Tinkeriot.com

• 🎥 YouTube Demo — ESP32 + MCP + LLM Integration

• 📘 Tasmota Commands Documentation

• 🧩 Model Context Protocol (MCP) SDK

🧠 Concept Summary

This project proves that intelligence in IoT doesn’t need more APIs — it needs context.

By combining:

• Tasmota’s readable command interface,

• MCP’s standardized AI communication layer, and

• ESP32’s hardware flexibility,

you get a device that can understand and act on intent, not just follow hardcoded rules.

📜 License

MIT License © 2025 [Your Name or tinkeriot.com]