Astronomy AI - Topography Analysis System

A simple and powerful system for analyzing locations for astronomy purposes, including elevation data and telescope obstruction analysis.

🚀 Quick Start

Step 1: Install Dependencies

pip install requests

Step 2: Run the System

python demo.py

📋 Features

• Elevation Analysis - Get elevation data for any location
• Location Parsing - Supports addresses and coordinates
• Quality Assessment - Evaluates location quality for astronomy
• Recommendations - Provides telescope orientation suggestions
• Multiple APIs - Uses free elevation and geocoding services

🛰️ Model Context Protocol (MCP) Server

The Astronomy Topography System includes a built-in Model Context Protocol (MCP) server for advanced integrations and automation.

What is the MCP Server?

• The MCP server allows external programs to connect via TCP and send analysis requests in real time.
• It uses a standard protocol for context management, configuration, and model execution.
• Useful for automation, remote control, or integrating with other AI/ML systems.

How to Start the MCP Server

From your project directory, run:

python -m astronomy_topography_system.src.mcp_server

Or, if you expose it via a CLI or entry point, use that command.

Configuration

• The server reads its settings from mcp_config.json (host, port, model parameters, etc.).
• Example config (src/mcp_config.json):

  {
    "model": "TopographySystem",
    "server": { "host": "127.0.0.1", "port": 65432 },
    "model_parameters": { "radius_km": 10, "observer_height": 2.0, "telescope_height": 1.5 },
    "user_input_mode": "manual",
    "logging": { "level": "INFO", "log_to_file": false }
  }
  

Protocol

• Client sends:

  { "context": {"user": "test"}, "query": "51.5, -0.1" }
  

• Server responds:

  { "result": { ...analysis result... } }
  

• All messages are JSON and newline-terminated (\n).

Example Client (Python)

import socket, json
s = socket.create_connection(("127.0.0.1", 65432))
msg = json.dumps({"context": {"user": "test"}, "query": "51.5, -0.1"}) + "\n"
s.sendall(msg.encode())
resp = s.recv(4096)
print(resp.decode())
s.close()

Extending the MCP Server

• You can implement your own model by following the ModelContextProtocol interface in model_context_protocol.py.
• The default model is TopographySystem, but you can swap in your own for custom logic.

---

🎯 How to Use

1. Run the program:

   python demo.py
   

2. Enter a location:

   • Address: "Mount Wilson Observatory, California"
   • Coordinates: "34.0522, -118.2437"
   • City: "Denver, Colorado"

3. Get results:

   • Elevation data
   • Location quality assessment
   • Telescope recommendations
   • Suggestions for better viewing

📊 Example Output

🌌 Astronomy AI - Topography Analysis System
==================================================

Example locations you can analyze:
   1. Mount Wilson Observatory, California
   2. 40.7589, -73.9851
   3. 34.0522, -118.2437
   4. Denver, Colorado
   5. Flagstaff, Arizona

Or enter your own location (address or coordinates):

Enter location (or 'quit' to exit): Flagstaff, Arizona

🔍 Analyzing location: Flagstaff, Arizona
Fetching elevation data...
Performing analysis...

============================================================
ASTRONOMY AI - LOCATION ANALYSIS RESULTS
============================================================

📍 Location: Flagstaff, Coconino County, Arizona, USA
   Coordinates: 35.1983, -111.6513

🏔️  Elevation Analysis:
   Elevation: 2106m
   Quality: Excellent

📊 Analysis:
   Location quality: Excellent
   Recommendation: High elevation - great for astronomy!

💡 Recommendations:
   Location quality: Excellent
   Telescope orientation: Point telescope toward the horizon for best views

💡 Suggestions:
   • Current elevation: 2106m
   • High elevation - great for astronomy!
   • Consider checking weather conditions
   • Look for areas with minimal light pollution
============================================================

🔧 Installation

Minimal Installation (Recommended)

pip install requests

Full Installation (Optional)

pip install requests python-dotenv

📁 Files

• demo.py - Main application
• requirements.txt - Python dependencies
• README.md - This file

🌟 Features Explained

Elevation Analysis

• Fetches elevation data from multiple free APIs
• Provides elevation quality assessment
• Compares to ideal astronomy elevations

Location Parsing

• Supports various input formats:
  • Full addresses: "Mount Wilson Observatory, California"
  • Coordinates: "34.0522, -118.2437"
  • City names: "Denver, Colorado"

Quality Assessment

• Excellent: >2000m elevation
• Good: 1000-2000m elevation
• Fair: 500-1000m elevation
• Poor: <500m elevation

Recommendations

• Telescope orientation suggestions
• Weather considerations
• Light pollution advice
• Alternative location suggestions

🔍 APIs Used

• Open-Elevation API - Primary elevation data
• USGS National Map API - Fallback elevation data
• Nominatim (OpenStreetMap) - Geocoding services

All APIs are free and don't require API keys.

🛠️ Troubleshooting

Common Issues

1. "ModuleNotFoundError: No module named 'requests'"

   pip install requests
   

2. "Connection error"

   • Check your internet connection
   • Try again in a few minutes

3. "Location not found"

   • Try a different location name
   • Use coordinates instead of address

Getting Help

If you encounter any issues:

1. Make sure you have Python 3.7+ installed
2. Install the required dependencies
3. Check your internet connection
4. Try the example locations first

🎉 Success!

Once you see the interactive prompt, you're ready to analyze locations for astronomy purposes!

Enter any location and get instant elevation data, quality assessment, and telescope recommendations.