MCP Servers for IoT and Memory Management
LocalAbout MCP Servers for IoT and Memory Management
A repository of two MCP servers: one controls and monitors IoT devices, and the other stores and searches persistent memories with Mem0. It is intended for applications needing device operations or long-term memory through MCP.
Key features
- 01Send commands to IoT devices
- 02Query device states and status
- 03Subscribe to real-time device updates
- 04Use MQTT for IoT communication
- 05Save and retrieve persistent memories
- 06Search memories semantically
Use cases
- 01Home automation and smart building control
- 02Industrial IoT monitoring and remote device management
- 03Storing conversation history
- 04Adding contextual memory to AI applications
MCP support
Provides two MCP servers. The IoT server exposes device command, state, and update tools; the memory server exposes tools to save, retrieve, and semantically search memories.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEMCP Servers for IoT and Memory Management
This repository contains two Model Context Protocol (MCP) servers:
- IoT Device Control MCP Server
- 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 deviceget_device_state: Get the current state of an IoT devicesubscribe_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 memoryget_all_memories: Get all stored memories for the usersearch_memories: Search memories using semantic search
Getting Started
- Clone this repository
- Install dependencies:
pip install -r requirements.txt - Create a
.envfile based on the.env.exampletemplate - Run the IoT server:
python iot_mcp_server.py - 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 implementationmemory_mcp_server.py- Memory management MCP server implementationutils.py- Utility functions used by the serversrequirements.txt- Package dependencies.env.example- Template for environment variables configurationREADME.md- Documentation
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.