Nina_advanced_api_mcp
Interface for AI agents to use your astrophotography setup using N.I.N.A advanced api
Documentation

Nina_advanced_api_mcp
Interface for AI agents to use your astrophotography setup using N.I.N.A (Beta)
N.I.N.A Model Context Protocol Server for Advanced API Plugin v2 (MCP)
A powerful interface for controlling N.I.N.A. (Nighttime Imaging 'N' Astronomy) software through its Advanced API NINA Advanced API . This Model Context Protocol Server (MCP) enables AI agents to interact with NINA using tools, providing new way to interact with your setup. Usage with your own responsibility.
๐ Features
- Complete Equipment Control for AI agents
- Cameras (capture, cooling, settings, connecting ....)
- Mounts (slewing, parking, tracking...)
- Focusers (movement, temperature compensation ... )
- Filter Wheels (filter selection, info ...)
- Domes (rotation, shutter control ...)
- Rotators (movement, sync...)
- ...
- AI Integration
- Natural language command processing
- Contextual help system
- Intelligent error responses
- Automated decision making
- **Most of the NINA advanced API v2 api interface endpoints supported
๐ Quick Start
Prerequisites
- Python 3.8 or higher
- NINA software with Advanced API plugin
- `uv` package manager
- AI agent with MCP support (e.g., Claude)
Installation
1. Install NINA Advanced API Plugin
# Install the plugins in NINA
# Enable and configure in NINA settings2. Clone Repository
git clone https://github.com/PaDev1/Nina_advanced_api_mcp.git
cd nina-mcp3. Set Environment Variables
# Create .env file
NINA_HOST=your_nina_host
NINA_PORT=1888
LOG_LEVEL=INFO
IMAGE_SAVE_DIR=~/Desktop/NINA_ImagesConfiguration
MCP Server Setup
Add to your AI agent's MCP configuration:
{
"mcpServers": {
"nina_advanced_mcp_api": {
"command": "uv",
"args": [
"run",
"--with",
"fastmcp,fastapi,uvicorn,pydantic,aiohttp,requests,python-dotenv",
"fastmcp",
"run",
"path/nina_advanced_mcp.py"
],
"env": {
"NINA_HOST": "NINA_IP",
"NINA_PORT": "1888",
"LOG_LEVEL": "INFO",
"IMAGE_SAVE_DIR": "~/Desktop/NINA_Images"
}
}
}
}๐ Usage
Basic AI Examples with Claude Destop
- Connect to nina
- read the setup
- connect my camera, mount, filter wheel and guider
- read the sequesces and let me select the sequence to start
AI Agent Commands
- "Take a 30-second exposure of M31"
- "Connect all equipment and start cooling the camera to -10ยฐC"
- "Start a sequence targeting NGC 7000"
- "Get the current equipment status"๐ API Documentation
Core Modules
Equipment Control
- Camera operations
- Mount control
- Focuser management
- Filter wheel control
- Dome automation
- Rotator functions
Imaging
- Capture configuration
- Image processing
- File management
- Statistics gathering
System
- Connection handling
- Status monitoring
- Error management
- Configuration
๐ค Contributing
Contributions are welcome! Please read our Contributing Guidelines first.
1. Fork the repository
2. Create your feature branch
3. Commit your changes
4. Push to the branch
5. Create a Pull Request
๐ Bug Reports
Found a bug? Please open an issue with:
- Detailed description
- Steps to reproduce
- Expected vs actual behavior
- System information
๐ License
This project is licensed under the MIT License - see the LICENSE file for details.
๐ Acknowledgments
- NINA - The core astronomy software
- NINA Advanced API - API documentation
๐ Related Projects
- Touch'N'Stars - WebApp for Mobile Control of NINA
- NINA Plugins - Official NINA plugin repository
Frequently asked questions
What is Nina_advanced_api_mcp?
Nina_advanced_api_mcp is Interface for AI agents to use your astrophotography setup using N.I.N.A advanced api
How do I install Nina_advanced_api_mcp?
Open the GitHub repository and follow its README. Most MCP servers are added to your client's MCP config, then called by your agent.
Is Nina_advanced_api_mcp open source?
Yes โ it is hosted on GitHub at https://github.com/PaDev1/Nina_advanced_api_mcp and has 12 stars.
Related MCP tools
AI Observability & Evaluation for the Model Context Protocol. Enhance AI assistants with powerful integrations. Jupyter Notebook-based implementation.
Model Context Protocol Servers
Pre-indexed code knowledge graph, auto syncs on code changes, for Claude Code, Codex, Gemini, Cursor, OpenCode, AntiGravity, Kiro, CoPilot, and Hermes Agent โ fewer tokens, fewer tool calls, 100% local
an open source, extensible AI agent that goes beyond code suggestions - install, execute, edit, and test with any LLM
The easy-to-use open source Business Intelligence and Embedded Analytics tool that lets everyone work with data :bar_chart:
The Open-Source Multimodal AI Agent Stack: Connecting Cutting-Edge AI Models and Agent Infra
Run your own MCP server? See who uses it and what to fix.
Measure it with TrackMCP