MCP Servers for IoT and Memory Management
About
This repository provides two Model Context Protocol (MCP) servers: one for controlling and monitoring IoT devices (smart lights, sensors, etc.) and another for persistent memory storage and retrieval using the Mem0 framework.
Details
- Author
- jordy33
- GitHub stars
- 2
- Downloads
- 169
- Categories
- Knowledge Base
Jump to
- Send commands to IoT devices and query their state
- Subscribe to real-time device updates via MQTT
- Save and retrieve long-term memory items
- Search memories using semantic search
- Support for SSE or stdio transport protocols
Clone the repository, install dependencies with pip install -r requirements.txt, create a .env file from the .env.example template, then run the IoT server with python iot_mcp_server.py and the memory server with python memory_mcp_server.py. Configure environment variables for MQTT broker, ports, and Mem0 API key as needed.
MCP Servers for IoT and Memory Management
This repository contains two Model Context Protocol (MCP) servers:
1. IoT Device Control MCP Server
2. Memory Management MCP Server
IoT Device Control MCP Server
A Model Context Protocol (MCP) server for controlling and monitoring IoT devices such as smart lights, sensors, and other connected devices.
Purpose
This server provides a standardized interface for IoT device control, monitoring, and state management through the Model Context Protocol.
Use Cases
- Home automation
- Industrial IoT monitoring
- Remote device management
- Smart building control systems
Features
- Send commands to IoT devices
- Query device state and status
- Subscribe to real-time device updates
- Support for MQTT protocol
API Tools
- send_command: Send a command to an IoT device
- get_device_state: Get the current state of an IoT device
- subscribe_to_updates: Subscribe to real-time updates from a device
Memory Management MCP Server
A Model Context Protocol (MCP) server for persistent memory storage and retrieval using the Mem0 framework.
Purpose
This server enables long-term memory storage and semantic search capabilities through the Model Context Protocol.
Use Cases
- Conversation history storage
- Knowledge management
- Contextual awareness in AI applications
- Persistent information storage
Features
- Save information to long-term memory
- Retrieve all stored memories
- Search memories using semantic search
API Tools
- save_memory: Save information to long-term memory
- get_all_memories: Get all stored memories for the user
- search_memories: Search memories using semantic search
Getting Started
1. Clone this repository
2. Install dependencies: pip install -r requirements.txt
3. Create a .env file based on the .env.example template
4. Run the IoT server: python iot_mcp_server.py
5. Run the Memory server: python memory_mcp_server.py
Environment Variables
IoT MCP Server
-MQTT_BROKER: MQTT broker address (default: "localhost")
- MQTT_PORT: MQTT broker port (default: 1883)
- HOST: Server host address (default: "0.0.0.0")
- PORT: Server port (default: "8090")
- TRANSPORT: Transport type, "sse" or "stdio" (default: "sse")
Memory MCP Server
-MEM0_API_KEY: API key for Mem0 service (optional)
- MEM0_ENDPOINT: Endpoint URL for Mem0 service (default: "https://api.mem0.ai")
- HOST: Server host address (default: "0.0.0.0")
- PORT: Server port (default: "8050")
- TRANSPORT: Transport type, "sse" or "stdio" (default: "sse")
Repository Structure
- iot_mcp_server.py - IoT device control MCP server implementation
- memory_mcp_server.py - Memory management MCP server implementation
- utils.py - Utility functions used by the servers
- requirements.txt - Package dependencies
- .env.example - Template for environment variables configuration
- README.md - Documentation
Sign in to leave a review
Use Google, GitHub, or an email account so ratings stay tied to real people.
No reviews posted yet.


