by pigeek
AndroidTVMCP: AI server to control Android TV — remote control, playback, app management, voice control and device statu
Enables AI assistants to control Android TV devices through MCP, providing remote control functionality like navigation, playback, and app management.
AndroidTVMCP is a community-built MCP server published by pigeek that provides AI assistants with tools and capabilities via the Model Context Protocol. AndroidTVMCP: AI server to control Android TV — remote control, playback, app management, voice control and device statu It is categorized under other, developer tools.
You can install AndroidTVMCP in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
MIT
AndroidTVMCP is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Share your MCP server with the developer community
AndroidTVMCP has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
AndroidTVMCP is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
Strong directory entry: AndroidTVMCP surfaces stars and publisher context so we could sanity-check maintenance before adopting.
AndroidTVMCP is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
According to our notes, AndroidTVMCP benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
Strong directory entry: AndroidTVMCP surfaces stars and publisher context so we could sanity-check maintenance before adopting.
AndroidTVMCP has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
According to our notes, AndroidTVMCP benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
I recommend AndroidTVMCP for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
AndroidTVMCP is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
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A Model Context Protocol (MCP) server that provides Android TV remote control functionality to AI assistants and other MCP clients.
AndroidTVMCP bridges Android TV remote control capabilities with the Model Context Protocol, enabling seamless integration of Android TV control into AI-powered workflows and automation systems.
# Create a virtual environment
python -m venv androidtvmcp-env
# Activate the virtual environment
# On Linux/macOS:
source androidtvmcp-env/bin/activate
# On Windows:
# androidtvmcp-env\Scripts\activate
# Install the package
pip install androidtvmcp
pip install androidtvmcp
androidtvmcp --host localhost --port 8080
Configure your MCP client to connect to the server
Use Android TV control tools through your AI assistant
Create a configuration file config.json:
{
"devices": {
"discovery": {
"enabled": true,
"timeout": 10
},
"connection": {
"timeout": 5,
"retry_attempts": 3
}
},
"mcp": {
"host": "localhost",
"port": 8080,
"transport": "stdio"
},
"logging": {
"level": "INFO",
"file": "androidtvmcp.log"
}
}
atv_navigate: Navigate Android TV interface (up, down, left, right, select, menu, back, home)atv_input_text: Send text input to Android TVatv_playback: Control media playback (play, pause, stop, fast_forward, rewind)atv_volume: Adjust volume (up, down, mute)atv_launch_app: Launch specific applicationsatv_get_apps: List available applicationsatv_switch_app: Switch between running applicationsatv_get_devices: List discovered Android TV devicesatv_get_status: Get current device status and stateatv_power: Power control (on, off, sleep)device://[device_id]/info: Device capabilities and informationdevice://[device_id]/status: Current device statusdevice://[device_id]/apps: Available applicationsstate://current_app: Currently active applicationstate://playback: Current playback statusstate://volume: Current volume level# Clone the repository
git clone https://github.com/pigeek/androidtvmcp.git
cd androidtvmcp
# Create and activate virtual environment
python -m venv venv
# Activate the virtual environment
# On Linux/macOS:
source venv/bin/activate
# On Windows:
# venv\Scripts\activate
# Install in development mode with dev dependencies
pip install -e ".[dev]"
git clone https://github.com/pigeek/androidtvmcp.git
cd androidtvmcp
pip install -e ".[dev]"
pytest
The devtools/ directory contains standalone scripts for manual testing and validation:
cd devtools
python test_command_processor.py # Test command processor functionality
python test_mcp_client.py # Test MCP client-server communication
python test_mcp_integration.py # Test MCP server integration
See devtools/README.md for detailed information about each script.
black src/ tests/
isort src/ tests/
mypy src/
┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐
│ MCP Client │◄──►│ AndroidTVMCP │◄──►│ Android TV │
│ (AI Assistant) │ │ Server │ │ Devices │
└─────────────────┘ └─────────────────┘ └─────────────────┘
Device Not Found
Connection Failed
Commands Not Working
Enable debug logging:
androidtvmcp --log-level DEBUG
MIT License - see LICENSE file for details.
Prerequisites
Time Estimate
15-60 minutes depending on server complexity
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.