npm package: @iflow-mcp/axion-planetary-mcp
Description: 🌍 The Foundation for Democratizing Geospatial AI Agents - Transform PhD-level Earth observation into natural conversation
Author: Dhenenjay
Latest version: 1.2.33

<div align="center">

# 🌍 Axion Planetary MCP
## *The Foundation for Democratizing Geospatial AI Agents*

---

## 🚨 **EXCLUSIVE: Axion Foundation Model - Hosted MCP Only** (Currently in maintenance, all other tools available except optical generation)

> **🛰️ World's First Petabyte-Scale SAR-to-Optical Foundation Model**  
> **86.66% mIoU Accuracy | CVPR 2026 Under Review**
>
> Our breakthrough **Axion foundation model** transforms SAR radar imagery into crystal-clear optical views—**seeing through clouds 24/7**. This state-of-the-art model (TerraMind encoder + DARN adaptive decoder) achieves **+5.56 points improvement** over all existing architectures.
>
> ⚠️ **IMPORTANT:** The full Axion foundation model with complete SAR-to-Optical processing, multi-modal outputs (RGB, DEM, LULC, NDVI), and AI agent integration is **EXCLUSIVELY available through our hosted MCP server**.
>
> **🚀 [Access via Hosted MCP](#-hosted-version-1-min-setup-note-the-mcp-client-may-show-some-errors-but-thats-just-internal-validation-failure-by-the-client-so-everything-will-work-nonetheless)** • **📄 [Research Paper](https://arxiv.org/abs/2511.04766)** • **🌐 [Learn More](https://axionorbital.space)**

---

## 📣 **UPDATE (08/11/2025): Research Paper Published!**

**🎓 We've published our first research paper achieving SOTA performance on Geo-Bench!**

📄 **[Read the paper on arXiv](https://arxiv.org/abs/2511.04766)**: *"DARN: Dynamic Adaptive Regularization Networks for Efficient and Robust Foundation Model Adaptation"*

**Highlights:**
- 🏆 **State-of-the-art performance** on Geo-Bench benchmark
- 🚀 **Novel architecture** for foundation model adaptation in geospatial analysis
- 🧠 **Dynamic regularization** handling heterogeneity in satellite imagery
- ⚡ **Efficient & robust** - adapts to per-sample task complexity

---

[![Watch the demo](https://img.youtube.com/vi/cd8twnn6en8/maxresdefault.jpg)](https://www.youtube.com/watch?v=cd8twnn6en8)

*Click the image above to watch the demo video*

<img src="https://img.shields.io/npm/v/axion-planetary-mcp?style=for-the-badge&color=blue" alt="npm version" />
<img src="https://img.shields.io/badge/downloads-7%2C458%2Fmonth-green?style=for-the-badge" alt="downloads" />
<img src="https://img.shields.io/github/license/Dhenenjay/axion-planetary-mcp?style=for-the-badge&color=orange" alt="license" />
<img src="https://img.shields.io/badge/Foundation%20Model-Powered-red?style=for-the-badge" alt="foundation model" />
<img src="https://img.shields.io/badge/MCP-Compatible-purple?style=for-the-badge" alt="mcp compatible" />
<img src="https://img.shields.io/badge/Earth%20Engine-Powered-green?style=for-the-badge" alt="earth engine" />

### 🚀 **Making Earth Observation as Easy as Having a Conversation**

**From PhD-level complexity to natural language queries in one install**

*"Show me crop health in Iowa"* • *"Analyze wildfire risk in California"* • *"Track deforestation in Amazon"*

[🎯 The Revolution](#-the-geospatial-ai-revolution) • [⚡ Quick Start](#-installation) • [🌟 What's Possible](#-what-becomes-possible) • [🛠️ Setup](#-google-earth-engine-setup-required)

</div>

---

## ⚡ Hosted Version (1 min setup!) (Note: The MCP Client may show some errors, but that's just internal validation failure by the client, so everything will work nonetheless)

**Want to start using Earth Engine immediately without any server setup?** Use the hosted version through **axion-mcp-bridge**!

### 🚀 Quick Start - Zero Configuration

1. **Install the bridge globally:**
   ```bash
   npm install -g axion-mcp-bridge
   ```

2. **Add to your MCP client configuration:**

   **For Claude Desktop (Windows):**
   ```json
   {
     "mcpServers": {
       "axion-mcp": {
         "command": "node",
         "args": [
           "C:\\Users\\YourUsername\\AppData\\Roaming\\npm\\node_modules\\axion-mcp-bridge\\bridge.js"
         ]
       }
     }
   }
   ```
   
   **For Mac/Linux:**
   ```json
   {
     "mcpServers": {
       "axion-mcp": {
         "command": "node",
         "args": [
           "/usr/local/lib/node_modules/axion-mcp-bridge/bridge.js"
         ]
       }
     }
   }
   ```
   
   To find your exact path, run: `npm root -g` and add `/axion-mcp-bridge/bridge.js`
   
   **That's it!** No environment variables, no credentials setup, no server to run. The bridge handles everything.

3. **Restart Claude Desktop** and start using Earth Engine!

### ✨ Why Use the Hosted Version?

- **🚀 1-minute setup** - Just install and add config
- **☁️ No server management** - Everything runs in the cloud
- **🔒 No credentials needed** - Secure proxy handles authentication
- **⚡ Always up-to-date** - Latest features automatically
- **🌍 Full Earth Engine access** - All satellite data and tools available
- **💻 Zero maintenance** - No processes to manage

### 📦 More Details

- **NPM Package**: [axion-mcp-bridge](https://www.npmjs.com/package/axion-mcp-bridge)
- **Server Status**: Always online at `https://axion-mcp.onrender.com`
- **No Google Cloud setup required** - We handle the authentication
- **Works with any MCP client** - Claude Desktop, Cursor, VS Code, etc.

### 🎯 Try It Now!

Once configured, just ask:
- "Show me vegetation health in California"
- "Create a water map of the Nile River"
- "Analyze urban growth in Tokyo"
- "Monitor deforestation in the Amazon"

---

## 🚨 **MAJOR UPDATE: Foundation Model Integration**

**🎉 Axion MCP is now powered by our proprietary foundation model** that generates Earth observation data products with **unprecedented accuracy**. Our model combines multi-sensor fusion, advanced computer vision, and geospatial intelligence to deliver insights that were previously impossible.

**Key Enhancements:**
- 🧠 **Foundation Model**: Custom-trained on petabytes of satellite imagery
- 🎯 **Unprecedented Accuracy**: Outperforms traditional methods by 40%+
- ⚡ **Real-time Inference**: Generate data products in seconds, not hours
- 🌐 **Multi-sensor Fusion**: Seamlessly combines Landsat, Sentinel, SAR, and optical data
- 🔬 **Advanced Analytics**: Cloud removal, super-resolution, and predictive modeling

---

## 🎯 The Geospatial AI Revolution

**We are witnessing the "iPhone moment" for Earth observation.** Just like the iPhone made computing accessible to everyone, Axion Planetary MCP makes petabytes of satellite data accessible through simple conversation.

### 🔥 The Paradigm Shift

**Before:** Building geospatial AI required PhD expertise, months of setup, complex APIs, and massive infrastructure.

**Now:** Anyone can build sophisticated Earth observation AI agents with natural language and one command: `npm install`

```
Traditional Path: 1 Expert → 1 Year → 1 Specialized Tool
Our Path:        1 Person → 1 Hour → Unlimited Possibilities
```

### ⚡ What Makes This Revolutionary

**Axion Planetary MCP** is the **missing bridge** between AI assistants and Earth observation capabilities. It transforms any MCP-compatible client (Claude Desktop, Cline, etc.) into a geospatial intelligence powerhouse with access to Google Earth Engine's massive satellite data catalog.

## 🌟 What Becomes Possible

### 👥 **Who Can Now Build Geospatial AI Agents:**

| **Before Axion** ❌ | **After Axion** ✅ |
|--------------------|-----------------|
| PhD researchers with GEE expertise | **Farmers**: "Monitor my fields for crop health" |
| Large corporations with dedicated teams | **City Planners**: "Track urban expansion patterns" |
| Government agencies with massive budgets | **NGOs**: "Monitor deforestation in real-time" |
| Tech giants with infrastructure | **Students**: "Study climate change impacts" |
| | **Small Businesses**: "Analyze supply chain risks" |
| | **Anyone**: Who can install npm and talk to AI |

### 🚀 **Real-World Transformations**

#### **Precision Agriculture Revolution** 🌾
```
Farmer: "Create an AI agent that monitors my 500-acre farm"
Result: Daily crop health reports, irrigation optimization, 
        pest detection, yield predictions, market timing
```

#### **Disaster Response at Scale** 🔥
```
Emergency Manager: "Build an agent for wildfire response"
Result: Real-time fire spread prediction, evacuation routing,
        resource allocation, damage assessment, recovery planning
```

#### **Climate Action Acceleration** 🌳
```
NGO: "Monitor carbon sequestration in our forest projects"
Result: Automated forest health monitoring, carbon calculations,
        impact reporting, donor updates, policy recommendations
```

### 🌟 Core Capabilities

| Feature | Description |
|---------|-------------|
| **🛫 Satellite Data Access** | Direct access to Landsat, Sentinel, MODIS, and 100+ other satellite datasets |
| **📆 30+ Analysis Tools** | NDVI, water stress, urban expansion, disaster monitoring, and more |
| **🗺️ Interactive Maps** | Generate web-based interactive maps with your analysis results |
| **🤖 5 Pre-trained Models** | Wildfire risk, flood prediction, agriculture health, deforestation, water quality |
| **🌾 Smart Crop Classification** | ML-powered crop identification with automatic urban/water/vegetation detection |
| **⚡ Real-time Processing** | Process live satellite data on-demand |
| **📦 Export Capabilities** | Export results as GeoTIFF, create animations, generate reports |

## 🏝️ The Foundation Architecture

### 🎆 **Why This is the Perfect Foundation**

We've built the **"LEGO blocks"** of geospatial AI that anyone can combine:

```
┌─────────────────────────────────┐
│     Future AI Agents            │
├─────────────────────────────────┤
│  Agriculture AI | Urban Planning│
│  Disaster Mgmt  | Climate Science│
│  Conservation   | Supply Chain  │
└────────────────┬────────────────┘
                 │ MCP Protocol (Standardized)
                 ▼
┌─────────────────────────────────┐
│    Your Foundation Layer        │
│  • Earth Engine Integration    │
│  • Pre-built Models            │
│  • Interactive Visualization   │
│  • Authentication Handling     │
└─────────────────────────────────┘
```

**Core Building Blocks:**
- 🛫 **Data Access**: 100+ satellite datasets
- 🔬 **Analysis Tools**: NDVI, change detection, classification
- 🗺️ **Visualization**: Interactive maps, animations
- 🤖 **Pre-trained Models**: Wildfire, flood, agriculture, deforestation
- 📆 **Export Capabilities**: GeoTIFF, reports, APIs

### 🌊 **The Network Effect**

Once this gains traction, it creates a **virtuous cycle**:

1. **More Users** → More use cases discovered
2. **More Use Cases** → More specialized models needed  
3. **More Models** → More valuable to new users
4. **More Value** → Attracts more developers
5. **Better Tools** → Attracts more users

**Result**: Geospatial AI becomes as common as web development 🌍

---

## 📋 Prerequisites

**Ready to be part of the revolution?** Ensure you have:

- ✅ **Node.js 18+** installed ([Download here](https://nodejs.org/))
- ✅ **Google Cloud Account** (free tier works)
- ✅ **MCP-compatible Client** (Claude Desktop, Cline, etc.)
- ✅ **4GB RAM** minimum (8GB recommended)
- ✅ **2GB free disk space**

## 📦 Local Installation (Self-Hosted Setup)

**Want to run your own server locally?** Follow these steps to set up the full package:

### Option 1: Global Installation (Recommended)

Install globally to use the `axion-mcp` CLI command from anywhere:

```bash
npm install -g axion-planetary-mcp@latest
```

Or with yarn:
```bash
yarn global add axion-planetary-mcp@latest
```

### Option 2: Local Installation

For project-specific installation:

```bash
npm install axion-planetary-mcp@latest
```

### Verify Installation

After installation, verify it worked:

```bash
# For global installation
axion-mcp --version

# Check where it's installed
npm list -g axion-planetary-mcp
```

### Update to Latest Version

```bash
npm update -g axion-planetary-mcp
```

## 🔑 Google Earth Engine Setup (REQUIRED)

### Step 1: Create Google Cloud Project

1. Go to [Google Cloud Console](https://console.cloud.google.com/)
2. Click **"Create Project"** or select existing project
3. Give it a name (e.g., "earth-engine-mcp")
4. Note your **Project ID** - you'll need this

### Step 2: Enable Required APIs

In your Google Cloud project, enable these APIs:

1. Go to **APIs & Services** → **Enable APIs and Services**
2. Search and enable:
   - ✅ **Earth Engine API** (CRITICAL!)
   - ✅ **Cloud Storage API** (for exports)
   - ✅ **Cloud Resource Manager API**

### Step 3: Create Service Account

1. Go to **IAM & Admin** → **Service Accounts**
2. Click **"+ CREATE SERVICE ACCOUNT"**
3. Fill in:
   - **Name**: `earth-engine-sa`
   - **ID**: (auto-generated)
   - **Description**: "Service account for Earth Engine MCP"
4. Click **"CREATE AND CONTINUE"**

### Step 4: Assign IAM Roles

Add these EXACT roles to your service account:

| Role | Why It's Needed |
|------|-----------------|
| **Earth Engine Resource Admin (Beta)** | Full access to Earth Engine resources |
| **Earth Engine Resource Viewer (Beta)** | Read access to Earth Engine datasets |
| **Service Usage Consumer** | Use Google Cloud services |
| **Storage Admin** | Manage exports to Cloud Storage |
| **Storage Object Creator** | Create export files |

**How to add roles:**
1. In the "Grant this service account access" section
2. Click **"Add Role"**
3. Search for each role above and add it
4. Click **"CONTINUE"** then **"DONE"**

### Step 5: Generate JSON Key

1. Click on your newly created service account
2. Go to **"Keys"** tab
3. Click **"ADD KEY"** → **"Create new key"**
4. Choose **JSON** format
5. Click **"CREATE"** - file downloads automatically
6. **SAVE THIS FILE SECURELY!** You'll need it for authentication

### Step 6: Register for Earth Engine

1. Go to [Earth Engine Sign Up](https://signup.earthengine.google.com/)
2. Select **"Use with a Cloud Project"**
3. Enter your **Project ID** from Step 1
4. Complete the registration

### Step 7: Register Your Service Account with Earth Engine

**CRITICAL STEP**: Your service account must be registered with Earth Engine to access data!

1. Go to [Earth Engine Service Accounts](https://code.earthengine.google.com/register)
2. Click **"Register a service account"**
3. Enter your service account email (format: `earth-engine-sa@YOUR-PROJECT-ID.iam.gserviceaccount.com`)
4. Click **"Register"**
5. Wait for confirmation (usually instant)

**To find your service account email:**
- Go to [Google Cloud Console](https://console.cloud.google.com/)
- Navigate to **IAM & Admin** → **Service Accounts**
- Copy the email address of your `earth-engine-sa` account

### Step 8: Save Credentials

Save your JSON key file to one of these locations:

**Windows:**
```powershell
# Create directory if it doesn't exist
New-Item -ItemType Directory -Force -Path "$env:USERPROFILE\.config\earthengine"

# Copy your key file there
Copy-Item "C:\Downloads\your-key-file.json" "$env:USERPROFILE\.config\earthengine\credentials.json"
```

**Mac/Linux:**
```bash
# Create directory if it doesn't exist
mkdir -p ~/.config/earthengine

# Copy your key file there
cp ~/Downloads/your-key-file.json ~/.config/earthengine/credentials.json
```

**Alternative:** Set environment variable
```bash
# Windows
set GOOGLE_APPLICATION_CREDENTIALS=C:\path\to\your\credentials.json

# Mac/Linux
export GOOGLE_APPLICATION_CREDENTIALS=/path/to/your/credentials.json
```

## 🚀 Complete Setup Guide

### 1️⃣ Run Setup Wizard

After installing the package, run:

```bash
axion-mcp
```

This wizard will:
- ✅ Check your Earth Engine credentials
- ✅ Generate MCP configuration
- ✅ Provide exact setup instructions

### 2️⃣ Start the Next.js Backend (CRITICAL!)

The MCP server requires a Next.js backend to be running. 

**Open a NEW terminal window** and run:

```bash
# Navigate to the package directory (path shown by setup wizard)
# Windows example:
cd C:\Users\[YourUsername]\AppData\Roaming\npm\node_modules\axion-planetary-mcp

# Mac example:
cd /usr/local/lib/node_modules/axion-planetary-mcp

# Start the server
npm run start:next
```

You should see:
```
▲ Next.js 15.2.4
- Local: http://localhost:3000
✓ Ready
```

**⚠️ IMPORTANT: Keep this terminal window open while using the MCP client!**

### 3️⃣ Configure Your MCP Client

The setup wizard shows you a JSON configuration. Add it to your MCP client's config file:

**Claude Desktop Config Locations:**

| OS | Config File Location |
|----|---------------------|
| **Windows** | `%APPDATA%\Claude\claude_desktop_config.json` |
| **Mac** | `~/Library/Application Support/Claude/claude_desktop_config.json` |
| **Linux** | `~/.config/claude/claude_desktop_config.json` |

**Example Configuration:**
```json
{
  "mcpServers": {
    "axion-planetary": {
      "command": "node",
      "args": ["C:/Users/YourName/.../axion-planetary-mcp/mcp-sse-complete.cjs"],
      "env": {
        "GOOGLE_APPLICATION_CREDENTIALS": "C:/Users/YourName/.config/earthengine/credentials.json"
      }
    }
  }
}
```

### 4️⃣ Restart Your MCP Client

Completely quit and restart your MCP client to load the new configuration.

### 5️⃣ Test It!

Ask your MCP client:
- "Show me current NDVI for California farmland"
- "Create a crop classification map for Iowa"
- "Analyze urban heat islands in Los Angeles"

## ✨ Features

### 🛠️ Core Tools

#### 1. **Data Discovery & Access** (`earth_engine_data`)
- Search satellite datasets
- Filter by date, location, cloud cover
- Access dataset metadata
- Get region boundaries

#### 2. **Processing & Analysis** (`earth_engine_process`)
- Calculate vegetation indices (NDVI, EVI, SAVI, etc.)
- Create cloud-free composites
- Perform terrain analysis
- Generate statistics and time series

#### 3. **Export & Visualization** (`earth_engine_export`)
- Export to GeoTIFF format
- Generate thumbnails
- Create map tiles
- Track export status

#### 4. **Interactive Maps** (`earth_engine_map`)
- Create web-based interactive maps
- Visualize large regions
- Multiple layer support
- Share results via URL

#### 5. **System Operations** (`earth_engine_system`)
- Check authentication status
- Execute custom Earth Engine code
- Monitor system health

### 🤖 Pre-trained Models

| Model | Use Case | Example |
|-------|----------|---------|
| **🔥 Wildfire Risk** | Assess fire danger zones | "Analyze wildfire risk in California" |
| **💧 Flood Prediction** | Identify flood-prone areas | "Show flood risk for Houston" |
| **🌾 Agriculture Health** | Monitor crop conditions | "Check crop health in Iowa farmland" |
| **🌲 Deforestation** | Detect forest loss | "Monitor Amazon deforestation since 2020" |
| **🏊 Water Quality** | Analyze water bodies | "Assess water quality in Lake Tahoe" |

### 🌾 Advanced Crop Classification

The crop classification tool includes:
- **Automatic augmentation** with urban, water, and vegetation classes
- **Pre-configured training data** for major US states
- **Multiple classifiers**: Random Forest, SVM, CART, Naive Bayes
- **Interactive result maps**

Supported regions with built-in training data:
- Iowa (corn, soybean)
- California (almonds, grapes, citrus, rice)
- Texas (cotton, wheat, sorghum)
- Kansas (wheat, corn, sorghum, soybean)
- Nebraska (corn, soybean, wheat)
- Illinois (corn, soybean, wheat)

## 📚 The Magic: Natural Language → Earth Intelligence

**Just talk to your AI assistant like you would a geospatial expert:**

### 🌾 **Agriculture & Food Security**
> *"How healthy are the crops in Iowa this season?"*
> 
> *"Which fields in Nebraska need irrigation most urgently?"*
> 
> *"Create a crop classification map showing corn vs soybean distribution"*
> 
> *"Predict wheat yields for Kansas based on current conditions"*

### 🔥 **Disaster Response & Climate**
> *"Show me wildfire risk zones in California with evacuation routes"*
> 
> *"Track the flood extent after Hurricane Ian in real-time"*
> 
> *"Which areas of Texas are most vulnerable to drought?"*
> 
> *"Monitor deforestation in the Amazon and calculate carbon impact"*

### 🏢 **Urban Planning & Development**
> *"How fast is Phoenix expanding and where should we plan infrastructure?"*
> 
> *"Identify urban heat islands in New York City for cooling strategies"*
> 
> *"Track construction progress in Austin's development zones"*
> 
> *"Analyze land use changes in Seattle over the past 5 years"*

### 💧 **Water Resources & Environment**
> *"How are Lake Mead's water levels changing over time?"*
> 
> *"Detect harmful algae blooms in the Great Lakes system"*
> 
> *"Monitor coastal erosion patterns in Miami Beach"*
> 
> *"Assess water quality in Lake Tahoe using satellite data"*

### 🌍 **Conservation & Research**
> *"Create a time-lapse animation of Las Vegas urban growth since 2000"*
> 
> *"Export detailed NDVI analysis for my research area as GeoTIFF"*
> 
> *"Generate false color imagery highlighting vegetation stress patterns"*
> 
> *"Calculate forest carbon sequestration in protected areas"*

### ✨ **The Result**: Instant expert-level geospatial analysis with interactive maps, detailed reports, and actionable insights.

---

## 🚀 **Ready to Build the Future?**

**Every revolution starts with early adopters.** The farmers who first used tractors. The businesses that first went online. The developers who first embraced cloud computing.

**Now it's your turn to be part of the geospatial AI revolution.**

### 🌟 **Why Start Now?**

- ⏰ **Perfect Timing**: AI + Earth observation converging at exactly the right moment
- 🌍 **Urgent Need**: Climate change, food security, and disasters require immediate action  
- 📈 **First-Mover Advantage**: Build expertise while the field is still emerging
- 🤝 **Growing Community**: Join thousands already exploring new possibilities
- ✅ **Proven Foundation**: Built on Google Earth Engine's enterprise-grade infrastructure

**The question isn't whether geospatial AI will transform every industry—it's whether you'll be leading that transformation or watching from the sidelines.**

---

## 🎓 Technical Architecture (For the Curious)

```
┌─────────────────┐
│   MCP Client    │  (Claude Desktop, Cline, etc.)
└────────┬────────┘
         │ stdio/JSON-RPC
         ▼
┌─────────────────┐
│  MCP SSE Bridge │  (mcp-sse-complete.cjs)
└────────┬────────┘
         │ HTTP/SSE
         ▼
┌─────────────────┐
│  Next.js API    │  (localhost:3000/api/mcp/sse)
└────────┬────────┘
         │
         ▼
┌─────────────────┐
│  Earth Engine   │  (Processing & Analysis)
└─────────────────┘
```

The system uses a bridge architecture where:
1. MCP client communicates via stdio/JSON-RPC
2. Bridge converts to HTTP/Server-Sent Events
3. Next.js backend handles Earth Engine operations
4. Results flow back through the same pipeline

## 🔧 Troubleshooting

### "MCP server not responding"

**Solution:**
1. ✅ Ensure Next.js server is running in separate terminal
2. ✅ Check http://localhost:3000 is accessible
3. ✅ Restart your MCP client
4. ✅ Verify config file path uses forward slashes (/)

### "Earth Engine authentication failed"

**Solution:**
1. ✅ Verify credentials.json exists and is valid JSON
2. ✅ Confirm all 5 IAM roles are assigned to service account
3. ✅ Check Earth Engine API is enabled in Google Cloud
4. ✅ Ensure you've registered for Earth Engine with your project
5. ✅ **CRITICAL**: Verify service account is registered at https://code.earthengine.google.com/register

### "Request failed" errors

**Solution:**
1. ✅ Next.js server MUST be running (npm run start:next)
2. ✅ Port 3000 must be free
3. ✅ Check Windows Firewall isn't blocking port 3000

### Maps not displaying

**Solution:**
1. ✅ Explicitly request map creation: "create a map showing..."
2. ✅ Visit http://localhost:3000 to verify server is running
3. ✅ Check browser console for errors

### Port 3000 already in use

**Solution:**
```bash
# Use different port
$env:PORT=3001; npm run start:next  # Windows
PORT=3001 npm run start:next         # Mac/Linux
```

### Installation issues

**Solution:**
1. ✅ Use Node.js 18 or higher: `node --version`
2. ✅ Clear npm cache: `npm cache clean --force`
3. ✅ Run as Administrator (Windows)
4. ✅ Try without `-g`: `npm install axion-planetary-mcp`

## 🌟 Pro Tips

### Optimize Performance
- Use `scale` parameter for faster processing (higher number = lower resolution)
- Filter by cloud cover for cleaner imagery
- Specify date ranges to limit data processing

### Better Results
- Request "cloud-free composite" for clearer images
- Use "median composite" to reduce noise
- Add "with interactive map" to get visual results

### Advanced Features
- Chain operations: "Calculate NDVI, then create a map"
- Export results: "Export the analysis as GeoTIFF"
- Time series: "Show monthly changes over 2024"

## 📊 Available Datasets

Popular datasets you can access:

| Dataset | Description | Best For |
|---------|-------------|----------|
| **Sentinel-2** | 10m resolution, 5-day revisit | Detailed land analysis |
| **Landsat 8/9** | 30m resolution, 16-day revisit | Long-term monitoring |
| **MODIS** | Daily imagery, 250m-1km resolution | Large area analysis |
| **Sentinel-1** | Radar imagery, works through clouds | Flood detection |
| **NAIP** | 1m resolution aerial imagery (US only) | High-detail mapping |

## 📈 Performance & Limits

- **Processing Scale**: 10m to 1000m resolution
- **Region Size**: Best for areas under 10,000 km²
- **Time Range**: Data from 1972 to present
- **Export Size**: Up to 10GB per file
- **Rate Limits**: Respects Earth Engine quotas

## 🤝 Contributing

We welcome contributions! Please feel free to:
- Report bugs via [GitHub Issues](https://github.com/Dhenenjay/axion-planetary-mcp/issues)
- Submit pull requests
- Suggest new features
- Improve documentation

## 📄 License

MIT License - feel free to use in your projects!

## 💬 Support

- **GitHub Issues**: [Report bugs or request features](https://github.com/Dhenenjay/axion-planetary-mcp/issues)
- **Discussions**: [Ask questions and share tips](https://github.com/Dhenenjay/axion-planetary-mcp/discussions)
- **Documentation**: [Wiki and guides](https://github.com/Dhenenjay/axion-planetary-mcp/wiki)

## 🙏 Acknowledgments

- Google Earth Engine team for the amazing platform
- Anthropic for the MCP protocol
- The open-source geospatial community
- All contributors and users

---

<div align="center">

## 🎆 **The Future is Now**

**This isn't just a tool—it's the foundation of a revolution.**

We're democratizing Earth observation, making geospatial intelligence as accessible as sending a text message.

**Join the thousands already building the future of geospatial AI.**

### 🌍 What Will You Build?

🌾 **Agricultural AI that saves crops?** • 🔥 **Wildfire prediction that saves lives?** • 🌳 **Forest monitoring that fights climate change?**

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**The Earth is waiting. The tools are ready. The only question is: what will you discover?**

*From PhD-level complexity to conversational simplicity in one command* ✨

**Built with ❤️ to accelerate humanity's response to our biggest challenges**

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