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VSCode Setup

Configure SkyFi MCP Server with Visual Studio Code for extensible development workflows with satellite imagery integration.

Overview​

Visual Studio Code is a popular, extensible code editor with rich ecosystem support. With SkyFi MCP integration, you can access satellite imagery and geospatial tools directly within your familiar VSCode development environment.

What You'll Get​

  • Rich Extension Ecosystem - Integrate with geospatial extensions
  • 21 Satellite & Geo Tools - Full SkyFi + OpenStreetMap toolkit
  • Customizable Interface - Adapt to your development workflow
  • Debugging Support - Debug geospatial applications with satellite context

Prerequisites​

  • Visual Studio Code installed (Download here)
  • SkyFi MCP Server installed (Installation Guide)
  • SkyFi API credentials from your account
  • MCP Extension for VSCode (available in marketplace)

Step-by-Step Setup​

1. Install MCP Extension​

  1. Open VSCode
  2. Open Extensions view (Ctrl/Cmd + Shift + X)
  3. Search for "MCP" or "Model Context Protocol"
  4. Install the official MCP extension
  5. Reload VSCode to activate the extension
Extension Availability

If the MCP extension isn't available yet in the marketplace, you can install it manually from a .vsix file or use the development version from the MCP repository.

2. Configuration Methods​

Choose your preferred configuration approach:

Global User Settings​

Configure SkyFi MCP for all projects globally:

  1. Open Settings (Ctrl/Cmd + ,)
  2. Search for "mcp"
  3. Edit in settings.json:
Global settings.json
{
  "mcp.servers": {
    "skyfi": {
      "command": "/full/path/to/your/venv/bin/python",
      "args": ["-m", "mcp_skyfi"],
      "cwd": "/full/path/to/your/project",
      "env": {
        "SKYFI_API_KEY": "your-email@example.com:your-api-key-hash",
        "SKYFI_URL": "https://app.skyfi.com/platform-api/pricing",
        "OPENWEATHER_API_KEY": "your-openweather-key"
      }
    }
  },
  "mcp.trace.server": "verbose",
  "mcp.autoStart": true
}

3. Find Your Python Path​

Determine the correct Python executable path:

# Virtual environment (recommended)
which python

# System Python
which python3

# From within VSCode integrated terminal
python -c "import sys; print(sys.executable)"

# Using VSCode Python extension
# Open Command Palette (Ctrl/Cmd + Shift + P)
# Type: "Python: Select Interpreter"
# Copy the selected interpreter path

4. VSCode Integration Features​

Python Extension Integration​

Python-optimized settings.json
{
  "mcp.servers": {
    "skyfi": {
      "command": "${config:python.pythonPath}",
      "args": ["-m", "mcp_skyfi"],
      "env": {
        "SKYFI_API_KEY": "your-email@example.com:your-api-key-hash",
        "SKYFI_URL": "https://app.skyfi.com/platform-api/pricing"
      }
    }
  },
  "python.defaultInterpreterPath": "/path/to/your/venv/bin/python",
  "python.terminal.activateEnvironment": true,
  "python.linting.enabled": true,
  "python.formatting.provider": "black"
}

Jupyter Integration​

Jupyter-enabled settings.json
{
  "mcp.servers": {
    "skyfi": {
      "command": "${config:python.pythonPath}",
      "args": ["-m", "mcp_skyfi"],
      "env": {
        "SKYFI_API_KEY": "your-email@example.com:your-api-key-hash",
        "SKYFI_URL": "https://app.skyfi.com/platform-api/pricing"
      }
    }
  },
  "jupyter.jupyterServerType": "local",
  "jupyter.notebookFileRoot": "${workspaceFolder}",
  "mcp.jupyterIntegration": true
}

5. Configuration Examples​

Example 1: Data Science Project​

Data Science .vscode/settings.json
{
  "mcp.servers": {
    "skyfi": {
      "command": "/Users/scientist/anaconda3/envs/geoai/bin/python",
      "args": ["-m", "mcp_skyfi"],
      "env": {
        "SKYFI_API_KEY": "researcher@university.edu:research-key-hash",
        "SKYFI_URL": "https://app.skyfi.com/platform-api/pricing",
        "OPENWEATHER_API_KEY": "weather-research-key",
        "MCP_LOG_LEVEL": "DEBUG"
      }
    }
  },
  "python.defaultInterpreterPath": "/Users/scientist/anaconda3/envs/geoai/bin/python",
  "jupyter.jupyterServerType": "local",
  "files.associations": {
    "*.geojson": "json"
  }
}

Example 2: Web Development Project​

Web Dev .vscode/settings.json
{
  "mcp.servers": {
    "skyfi": {
      "command": "/home/developer/projects/webapp/venv/bin/python",
      "args": ["-m", "mcp_skyfi"],
      "env": {
        "SKYFI_API_KEY": "webapp@company.com:webapp-key-hash",
        "SKYFI_URL": "https://app.skyfi.com/platform-api/pricing"
      }
    }
  },
  "python.defaultInterpreterPath": "./venv/bin/python",
  "typescript.suggest.autoImports": true,
  "javascript.suggest.autoImports": true
}

Example 3: Multi-Language Project​

Multi-language .vscode/settings.json
{
  "mcp.servers": {
    "skyfi": {
      "command": "python",
      "args": ["-m", "mcp_skyfi"],
      "env": {
        "SKYFI_API_KEY": "multidev@company.com:multi-key-hash",
        "SKYFI_URL": "https://app.skyfi.com/platform-api/pricing"
      }
    }
  },
  "files.associations": {
    "*.geojson": "json",
    "*.gpx": "xml",
    "*.kml": "xml"
  },
  "emmet.includeLanguages": {
    "javascript": "javascriptreact"
  }
}

Verification​

Test MCP Integration​

  1. Open Command Palette (Ctrl/Cmd + Shift + P)
  2. Search for "MCP" commands
  3. Run "MCP: List Tools" or equivalent command

Expected Result: Should show 21 tools (13 SkyFi + 8 OpenStreetMap tools).

Test with VSCode Chat/AI​

If you have GitHub Copilot or another AI extension:

Ask your AI assistant: "List all available MCP tools and their categories"

Test in Integrated Terminal​

# Test server directly
python -m mcp_skyfi --config-check

# Test tool discovery
python -c "
from mcp_skyfi.servers.main import main_mcp
tools = main_mcp.list_tools()
print(f'Found {len(tools)} tools')
for tool in tools[:5]:
    print(f'  - {tool.name}')
"

Development Features​

Code Completion​

With geospatial libraries installed, you'll get enhanced IntelliSense for:

  • Geospatial data structures (GeoJSON, Shapely geometries)
  • Coordinate systems and projections (EPSG codes)
  • Satellite imagery formats (GeoTIFF, COG)
  • API integration patterns

Debugging Support​

Debug Configuration​

.vscode/launch.json
{
  "version": "0.2.0",
  "configurations": [
    {
      "name": "Debug SkyFi Script",
      "type": "python",
      "request": "launch",
      "program": "${file}",
      "console": "integratedTerminal",
      "env": {
        "SKYFI_API_KEY": "your-email@example.com:your-api-key-hash",
        "SKYFI_URL": "https://app.skyfi.com/platform-api/pricing",
        "MCP_LOG_LEVEL": "DEBUG"
      }
    },
    {
      "name": "Debug MCP Server",
      "type": "python",
      "request": "launch",
      "module": "mcp_skyfi",
      "console": "integratedTerminal",
      "env": {
        "SKYFI_API_KEY": "your-email@example.com:your-api-key-hash",
        "MCP_LOG_LEVEL": "DEBUG"
      }
    }
  ]
}

Task Integration​

.vscode/tasks.json
{
  "version": "2.0.0",
  "tasks": [
    {
      "label": "Test SkyFi MCP",
      "type": "shell",
      "command": "python",
      "args": ["-m", "mcp_skyfi", "--config-check"],
      "group": "test",
      "presentation": {
        "echo": true,
        "reveal": "always",
        "focus": false,
        "panel": "shared"
      }
    },
    {
      "label": "Start MCP Server",
      "type": "shell", 
      "command": "python",
      "args": ["-m", "mcp_skyfi", "--transport", "stdio"],
      "group": "build",
      "isBackground": true
    }
  ]
}

Snippets​

Create custom snippets for geospatial development:

.vscode/snippets/geospatial.json
{
  "SkyFi Archive Search": {
    "prefix": "skyfi-search",
    "body": [
      "# Search for satellite imagery",
      "result = await mcp_client.call_tool('skyfi_archive_search', {",
      "    'aoi': $1,",
      "    'start_date': '$2',", 
      "    'end_date': '$3',",
      "    'cloud_cover_max': $4",
      "})",
      "print(f'Found {len(result)} images')"
    ],
    "description": "SkyFi archive search template"
  },
  "OSM Geocoding": {
    "prefix": "osm-geocode",
    "body": [
      "# Geocode address",
      "result = await mcp_client.call_tool('osm_forward_geocode', {",
      "    'query': '$1'",
      "})",
      "lat, lon = result['latitude'], result['longitude']",
      "print(f'Coordinates: {lat}, {lon}')"
    ],
    "description": "OSM geocoding template"
  }
}

Extensions Integration​

For optimal geospatial development with SkyFi MCP:

extensions.json
{
  "recommendations": [
    "ms-python.python",
    "ms-python.vscode-pylance",
    "ms-toolsai.jupyter",
    "ms-vscode.mcp-extension",
    "ms-vscode.hexeditor",
    "randomfractalsinc.geo-data-viewer",
    "ms-vscode-remote.remote-containers",
    "github.copilot",
    "ms-vscode.vscode-json"
  ]
}

Extension-Specific Configuration​

Geo Data Viewer Extension​

Geo viewer settings
{
  "geoDataViewer.maxFileSize": "100MB",
  "geoDataViewer.defaultMap": "satellite",
  "mcp.geoDataIntegration": true
}

Jupyter Extension​

Jupyter + MCP settings
{
  "jupyter.askForKernelRestart": false,
  "jupyter.interactiveWindowMode": "perFile",
  "mcp.jupyter.autoInjectTools": true,
  "mcp.jupyter.showToolsInAutocomplete": true
}

Advanced Configuration​

Multi-Root Workspace​

workspace.code-workspace
{
  "folders": [
    {
      "name": "Frontend",
      "path": "./frontend"
    },
    {
      "name": "Backend", 
      "path": "./backend"
    },
    {
      "name": "Data Analysis",
      "path": "./analysis"
    }
  ],
  "settings": {
    "mcp.servers": {
      "skyfi": {
        "command": "python",
        "args": ["-m", "mcp_skyfi"],
        "env": {
          "SKYFI_API_KEY": "multiproject@company.com:key-hash",
          "SKYFI_URL": "https://app.skyfi.com/platform-api/pricing"
        }
      }
    }
  }
}

Performance Optimization​

Performance-optimized settings
{
  "mcp.servers": {
    "skyfi": {
      "command": "python",
      "args": ["-m", "mcp_skyfi"],
      "env": {
        "SKYFI_API_KEY": "your-key",
        "MCP_POOL_SIZE": "10",
        "MCP_TIMEOUT": "60",
        "MCP_CACHE_ENABLED": "true"
      }
    }
  },
  "mcp.maxConcurrentRequests": 5,
  "mcp.requestTimeout": 30000,
  "files.watcherExclude": {
    "**/.git/objects/**": true,
    "**/node_modules/**": true,
    "**/.venv/**": true
  }
}

Troubleshooting​

Common Issues​

MCP Extension Not Loading​

Problem: MCP extension doesn't appear in extensions list Solutions:

  • Update VSCode to latest version
  • Check if extension is available in marketplace
  • Try installing from VSIX file
  • Restart VSCode completely

Python Interpreter Issues​

Problem: Wrong Python interpreter or environment Solutions:

  • Use Command Palette: "Python: Select Interpreter"
  • Check python.defaultInterpreterPath setting
  • Verify virtual environment activation
  • Use absolute paths in configuration

Tools Not Available​

Problem: MCP tools don't appear in IntelliSense or chat Solutions:

  • Check MCP server status in status bar
  • Verify Python path and working directory
  • Test server with python -m mcp_skyfi --config-check
  • Check output panel for MCP logs

Slow Performance​

Problem: VSCode becomes slow with MCP enabled Solutions:

  • Reduce mcp.maxConcurrentRequests
  • Increase mcp.requestTimeout
  • Enable file watcher exclusions
  • Use workspace settings instead of global

Debug Commands​

# Test MCP server
python -m mcp_skyfi --config-check

# Test tool discovery
python -c "
from mcp_skyfi.servers.main import main_mcp
tools = main_mcp.list_tools()
print(f'Tools: {len(tools)}')
"

# Check VSCode Python path
code --list-extensions | grep python

VSCode Output Panel​

Check the VSCode Output panel for MCP-related logs:

  1. Open Output panel (Ctrl/Cmd + Shift + U)
  2. Select "MCP" from dropdown
  3. Look for connection and error messages
  4. Check "Python" output for interpreter issues

Development Workflows​

Geospatial Data Analysis​

  1. Setup: Create Python environment with geospatial libraries
  2. Configuration: Configure SkyFi MCP for the project
  3. Development: Use Jupyter notebooks with MCP integration
  4. Visualization: Use geo data viewer extensions
  5. Debugging: Debug scripts with satellite data context

Web Application Development​

  1. Backend: Python/Flask API with SkyFi MCP integration
  2. Frontend: JavaScript/React with map visualization
  3. Testing: Test API endpoints with real satellite data
  4. Deployment: Deploy with environment-specific configurations

Data Science Pipeline​

  1. Data Collection: Use MCP tools to gather satellite imagery
  2. Processing: Analyze imagery with Python/NumPy/Pandas
  3. Visualization: Create maps and charts in Jupyter
  4. Modeling: Build ML models with geospatial features
  5. Deployment: Deploy models with VSCode Azure extensions

Next Steps​

Once VSCode is configured and working:

Start Developing​

  • Verification Guide - Test your setup
  • API Examples (coming soon) - Development patterns
  • Best Practices (coming soon) - VSCode optimization

Advanced Features​

  • Environment Variables (coming soon) - Configuration management
  • Authentication Methods (coming soon) - Secure integration
  • Performance Tuning (coming soon) - Optimization tips

Resources​

  • Architecture Overview (coming soon) - System design
  • Contributing (coming soon) - Help improve the project
  • Tools Reference (coming soon) - Explore all 21 tools

Support​

Need help with VSCode setup?

Developer's Choice!

VSCode with SkyFi MCP gives you the perfect blend of familiar development tools and powerful satellite imagery capabilities. Ideal for developers who want maximum customization and extension integration!