getting-started.md•3.96 kB
# Getting Started
This guide helps you install and run the GIS MCP Server quickly using pip (with uv) and shows how to connect it to your IDE/client.
### Prerequisites
- Python 3.10+
- Internet access to install packages
### Install via pip (with uv)
1. Create a virtual environment:
```bash
pip install uv
uv venv --python=3.10
```
2. Install the package:
```bash
uv pip install gis-mcp
```
3. Run the server:
```bash
gis-mcp
```
By default, the server runs in **STDIO transport mode**, which is ideal for local development and integration with Claude Desktop or Cursor IDE.
You can also run the server in **HTTP transport mode** for network deployments:
```bash
export GIS_MCP_TRANSPORT=http
export GIS_MCP_PORT=8080
gis-mcp
```
For more details on transport modes (STDIO vs HTTP), see the [HTTP Transport Configuration](http-transport.md) documentation.
### Connect to an MCP client
Claude Desktop (Windows):
```json
{
"mcpServers": {
"gis-mcp": {
"command": "C:\\Users\\YourUsername\\.venv\\Scripts\\gis-mcp",
"args": []
}
}
}
```
Claude Desktop (Linux/Mac):
```json
{
"mcpServers": {
"gis-mcp": {
"command": "/home/YourUsername/.venv/bin/gis-mcp",
"args": []
}
}
}
```
Cursor IDE (Windows) – `.cursor/mcp.json`:
```json
{
"mcpServers": {
"gis-mcp": {
"command": "C:\\Users\\YourUsername\\.venv\\Scripts\\gis-mcp",
"args": []
}
}
}
```
Cursor IDE (Linux/Mac) – `.cursor/mcp.json`:
```json
{
"mcpServers": {
"gis-mcp": {
"command": "/home/YourUsername/.venv/bin/gis-mcp",
"args": []
}
}
}
```
This video teaches you the installation of GIS MCP Server on your windows and Claude Desktop:
<iframe width="560" height="315" src="https://www.youtube.com/embed/1u_ra1Wp4es" frameborder="0" allowfullscreen></iframe>
Notes
- Replace `YourUsername` with your actual username
- Restart your IDE after adding configuration
### Optional Features & Extras
GIS MCP Server supports several optional features for specialized workflows. You can install these extras using pip with square brackets, e.g.:
```bash
uv pip install "gis-mcp[climate]"
```
Available extras:
- **climate**: For climate data access and processing (installs `cdsapi`)
- **ecology**: For ecological and biodiversity data (installs `pygbif`)
- **administrative-boundaries**: For working with global administrative boundaries (installs `pygadm`)
- **movement**: For movement and network analysis (installs `osmnx`)
- **satellite-imagery**: For searching and processing satellite imagery (installs `pystac-client`, `planetary-computer`, `xarray`, `stackstac`, `requests`)
- **land-cover**: For land cover data workflows (same as satellite-imagery)
- **all**: Installs all optional dependencies for full functionality
Example to install with multiple extras:
```bash
uv pip install "gis-mcp[climate,ecology,movement]"
```
See the `pyproject.toml` or documentation for the full list of extras and their included packages.
For more information on fetching external datasets (climate, ecology, movement, satellite imagery, and more), see the [Data Gathering guide](data-gathering/README.md).
### Build Your First GIS AI Agent
Ready to create your own AI agent that can perform geospatial operations? Our comprehensive tutorial will guide you from zero to hero!
👉 **[Build Your First GIS AI Agent with LangChain →](gis-ai-agent.md)**
Learn how to:
- Set up the GIS MCP server in HTTP mode
- Build a LangChain agent from scratch
- Connect your agent to GIS tools
- Use OpenRouter to access multiple AI models (DeepSeek, Gemini, GPT-4, Claude, etc.)
- Customize and extend your agent
Perfect for developers, data scientists, and anyone interested in building AI-powered geospatial applications.
### Next steps
- Explore the API Reference in the sidebar (Shapely, PyProj, GeoPandas, Rasterio, PySAL)
- Check Installations → Developers for editable installs
