Gis Mcp

✨ Want to perform accurate geospatial analysis in your chatbot? ✨ Install GIS-MCP and transform your AI's spatial capabilities!

A Model Context Protocol (MCP) server implementation that connects Large Language Models (LLMs) to GIS operations using GIS libraries, enabling AI assistants to perform geospatial operations and transformations.

🌐 Website: gis-mcp.com

> Current version is 0.14.0 (Beta): > > We welcome contributions and developers to join us in building this project.

🎥 Demo

📋 Table of Contents

• [Features](#-features)
• [Prerequisites](#-prerequisites)
• [Vibe Coding](#vibe-coding)
• [Installation](#-installation)
• [Docker Installation](#-docker-installation)
• [pip Installation](#-pip-installation)
• [Development Installation](#-development-installation)
• [Build Your First GIS AI Agent](#-build-your-first-gis-ai-agent)
• [Available Functions](#-available-functions)
• [Shapely Functions](#-shapely-functions-29-total)
• [PyProj Functions](#-pyproj-functions-13-total)
• [GeoPandas Functions](#-geopandas-functions-13-total)
• [Rasterio Functions](#-rasterio-functions-20-total)
• [PySAL Functions](#-pysal-functions-18-total)
• [Visualization Functions](#-visualization-functions-2-total)
• [Static Map Functions](#-static-map-functions-1-total)
• [Interactive Web Map Functions](#-interactive-web-map-functions-1-total)
• [Administrative Boundaries Functions](#-administrative-boundaries-functions-1-total)
• [Climate Data Functions](#-climate-data-functions-1-total)
• [Ecology Data Functions](#-ecology-data-functions-2-total)
• [Movement Data Functions](#-movement-data-functions-2-total)
• [Land Cover Data Functions](#-land-cover-data-functions-2-total)
• [Satellite Imagery Functions](#-satellite-imagery-functions-1-total)
• [Client Development](#-client-development)
• [Planned Features](#-planned-features)
• [Contributing](#-contributing)
• [License](#-license)
• [Related Projects](#-related-projects)
• [Support](#-support)
• [Badges](#-badges)

🚀 Features

GIS MCP Server empowers AI assistants with advanced geospatial intelligence. Key features include:

• 🔹 Comprehensive Geometry Operations – Perform intersection, union, buffer, difference, and other geometric transformations with ease.
• 🔹 Advanced Coordinate Transformations – Effortlessly reproject and transform geometries between coordinate reference systems.
• 🔹 Accurate Measurements – Compute distances, areas, lengths, and centroids precisely.
• 🔹 Spatial Analysis & Validation – Validate geometries, run proximity checks, and perform spatial overlays or joins.
• 🔹 Raster & Vector Support – Process raster layers, compute indices like NDVI, clip, resample, and merge with vector data.
• 🔹 Spatial Statistics & Modeling – Leverage PySAL for spatial autocorrelation, clustering, and neighborhood analysis.
• 🔹 Easy Integration – Connect seamlessly with MCP-compatible clients like Claude Desktop or Cursor IDE.
• 🔹 HTTP/SSE Transport – Run as HTTP service with RESTful storage endpoints for file upload/download operations.
• 🔹 Flexible & Extensible – Supports Python-based GIS libraries and is ready for custom tools or workflow extensions.

> 🌟 Tip: With GIS MCP Server, your AI can now “think spatially,” unlocking new capabilities for environmental analysis, mapping, and location intelligence.

📋 Prerequisites

• Python 3.10 or higher
• MCP-compatible client (like Claude Desktop or Cursor)
• Internet connection for package installation

Vibe Coding

If you’re building agents via vibe coding, use these context files in your editor so the LLM understands the GIS MCP server:

• llms.txt: summarized context for smaller windows.
• llms-full.txt: full context when your model has a larger window.

🛠 Installation

Choose the installation method that best suits your needs:

🐳 Docker Installation

GIS MCP Server can be run using Docker, which provides an isolated environment with all dependencies pre-installed.

Important: Both Dockerfile and Dockerfile.local have HTTP transport mode enabled by default. The server runs on port 9010 and is accessible at http://localhost:9010/mcp.

Using Dockerfile

The main Dockerfile installs the package from PyPI:

1. Build the Docker image:

docker build -t gis-mcp .

1. Run the container (HTTP mode is enabled by default):

docker run -p 9010:9010 gis-mcp

Using Dockerfile.local

The Dockerfile.local installs the package from local source files (useful for development or custom builds):

1. Build the Docker image:

docker build -f Dockerfile.local -t gis-mcp:local .

1. Run the container (HTTP mode is enabled by default):

docker run -p 9010:9010 gis-mcp:local

The server will be available at http://localhost:9010/mcp in HTTP transport mode.

For more details on Docker configuration and environment variables, see the [Docker installation guide](docs/install/docker.md).

📦 pip Installation

The pip installation is recommended for most users:

1. Install uv package manager:

pip install uv

1. Create the Virtual Environment (Python 3.10+):

uv venv --python=3.10

1. Activate the Virtual Environment:

On Windows (PowerShell):

.\.venv\Scripts\Activate.ps1

On Linux:

source .venv/bin/activate

1. Install the package:

uv pip install gis-mcp

Install with Visualization Features

To install with visualization capabilities (Folium and PyDeck for interactive maps):

uv pip install gis-mcp[visualize]

This will install additional dependencies:

• folium>=0.15.0 - For creating interactive web maps
• pydeck>=0.9.0 - For advanced 3D visualizations

1. Start the server:

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:

export GIS_MCP_TRANSPORT=http
export GIS_MCP_PORT=8080
gis-mcp

When running in HTTP or SSE transport mode, the following endpoints are available:

• MCP endpoint: http://host:port/mcp (HTTP) or http://host:port/sse (SSE)
• Storage endpoints:
• POST /storage/upload - Upload files to server storage
• GET /storage/download?path= - Download files from server storage
• GET /storage/list?path= - List files in server storage

For more details on transport modes and complete endpoint documentation, see:

• [HTTP Transport Configuration](docs/http-transport.md)
• [Server Endpoints](docs/endpoints.md)

pip Configuration

To use the pip installation with Claude or Cursor, add the following configuration:

Claude Desktop:

Windows:

{
  "mcpServers": {
    "gis-mcp": {
      "command": "C:\\Users\\YourUsername\\.venv\\Scripts\\gis-mcp",
      "args": []
    }
  }
}

Linux/Mac:

{
  "mcpServers": {
    "gis-mcp": {
      "command": "/home/YourUsername/.venv/bin/gis-mcp",
      "args": []
    }
  }
}

Cursor IDE (create .cursor/mcp.json):

Windows:

{
  "mcpServers": {
    "gis-mcp": {
      "command": "C:\\Users\\YourUsername\\.venv\\Scripts\\gis-mcp",
      "args": []
    }
  }
}

Linux/Mac:

{
  "mcpServers": {
    "gis-mcp": {
      "command": "/home/YourUsername/.venv/bin/gis-mcp",
      "args": []
    }
  }
}

After configuration:

1. Make sure to replace YourUsername with your actual username
2. For development installation, replace /path/to/gis-mcp with the actual path to your project
3. Restart your IDE to apply the changes
4. You can now use all GIS operations through Claude or Cursor!

🛠 Development Installation

For contributors and developers:

1. Install uv package manager:

pip install uv

1. Create the Virtual Environment:

uv venv --python=3.10

1. Install the package in development mode:

uv pip install -e .

1. Start the server:

python -m gis_mcp

Development Configuration

To use the development installation with Claude or Cursor, add the following configuration:

Claude Desktop:

Windows:

{
  "mcpServers": {
    "gis-mcp": {
      "command": "C:\\path\\to\\gis-mcp\\.venv\\Scripts\\python",
      "args": ["-m", "gis_mcp"]
    }
  }
}

Linux/Mac:

{
  "mcpServers": {
    "gis-mcp": {
      "command": "/path/to/gis-mcp/.venv/bin/python",
      "args": ["-m", "gis_mcp"]
    }
  }
}

Cursor IDE (create .cursor/mcp.json):

Windows:

{
  "mcpServers": {
    "gis-mcp": {
      "command": "C:\\path\\to\\gis-mcp\\.venv\\Scripts\\python",
      "args": ["-m", "gis_mcp"]
    }
  }
}

Linux/Mac:

{
  "mcpServers": {
    "gis-mcp": {
      "command": "/path/to/gis-mcp/.venv/bin/python",
      "args": ["-m", "gis_mcp"]
    }
  }
}

After configuration:

1. Make sure to replace YourUsername with your actual username
2. For development installation, replace /path/to/gis-mcp with the actual path to your project
3. Restart your IDE to apply the changes
4. You can now use all GIS operations through Claude or Cursor!

🤖 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!

What You'll Learn

• ✅ How to set up the GIS MCP server in HTTP mode
• ✅ How to build a LangChain agent from scratch
• ✅ How to connect your agent to GIS tools
• ✅ How to use OpenRouter to access multiple AI models (DeepSeek, Gemini, GPT-4, Claude, etc.)
• ✅ How to customize and extend your agent

Get Started

👉 Follow the complete tutorial →

📝 Read the Medium article →

🎥 Watch tutorials on YouTube →

The tutorial is beginner-friendly and requires no prior AI or GIS experience. You'll build a working agent that can:

• Calculate distances between points
• Transform coordinates between different systems
• Create buffers around locations
• Perform spatial analysis
• And much more!

Perfect for: Developers, data scientists, GIS professionals, and anyone interested in building AI-powered geospatial applications.

📚 Available Functions

This section provides a comprehensive list of all available functions organized by library.

🔷 Shapely Functions (29 total)

Basic Geometric Operations:

• buffer - Create buffer around geometry
• intersection - Find intersection of two geometries
• union - Combine two geometries
• difference - Find difference between geometries
• symmetric_difference - Find symmetric difference

Geometric Properties:

• convex_hull - Calculate convex

…

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: mahdin75
• Source: mahdin75/gis-mcp
• License: MIT
• Homepage: https://gis-mcp.com/

Install and usage instructions live in the source repository linked above.