Geoserver

GeoServer MCP Server

Version 0.5.0 (Beta) is under active development and will be released shortly. We are open to contributions and welcome developers to join us in building this project.

🎥 Demo

📋 Table of Contents

• Features
• Prerequisites
• Installation
  • Docker Installation
  • pip Installation
  • Development Installation
• File Storage and --storage Usage
• Available Tools
  • Resource Endpoints
  • Workspace Management
  • Datastore & Coveragestore Management
  • Layer Management
  • Layer Group Management
  • User & User Group Management
  • Feature Type & Attribute Management
  • Style Management
  • System & Service Operations
  • Style XML Utilities
• Client Development
  • List Workspaces
  • Get Layer Information
  • Query Features
  • Generate Map
• Planned Features
• Contributing
• License
• Related Projects
• Support
• Badges

🚀 Features

• 🔍 Query and manipulate GeoServer workspaces, layers, and styles
• 🗺️ Execute spatial queries on vector data
• 🎨 Generate map visualizations
• 🌐 Access OGC-compliant web services (WMS, WFS)
• 🛠️ Easy integration with MCP-compatible clients

📋 Prerequisites

• Python 3.10 or higher
• Running GeoServer instance with REST API enabled
• MCP-compatible client (like Claude Desktop or Cursor)
• Internet connection for package installation

🛠️ Installation

Choose the installation method that best suits your needs:

Installing via Smithery

To install GeoServer MCP Server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @mahdin75/geoserver-mcp --client claude

🛠️ Installation (Docker)

The Docker installation is the quickest and most isolated way to run the GeoServer MCP server. It's ideal for:

• Quick testing and evaluation
• Production deployments
• Environments where you want to avoid Python dependencies
• Consistent deployment across different systems

1. Run geoserver-mcp:

docker pull mahdin75/geoserver-mcp
docker run -d mahdin75/geoserver-mcp

1. Configure the clients:

If you are using Claude Desktop, edit claude_desktop_config.json If you are using Cursor, Create .cursor/mcp.json

{
  "mcpServers": {
    "geoserver-mcp": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "GEOSERVER_URL=http://localhost:8080/geoserver",
        "-e",
        "GEOSERVER_USER=admin",
        "-e",
        "GEOSERVER_PASSWORD=geoserver",
        "-p",
        "8080:8080",
        "mahdin75/geoserver-mcp"
      ]
    }
  }
}

🛠️ Installation (pip)

The pip installation is recommended for most users who want to run the server directly on their system. This method is best for:

• Regular users who want to run the server locally
• Systems where you have Python 3.10+ installed
• Users who want to customize the server configuration
• Development and testing purposes

1. Install uv package manager.

pip install uv

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

Linux/Mac:

uv venv --python=3.10

Windows PowerShell:

uv venv --python=3.10

1. Install the package using pip:

uv pip install geoserver-mcp

1. Configure GeoServer connection:

Linux/Mac:

export GEOSERVER_URL="http://localhost:8080/geoserver"
export GEOSERVER_USER="admin"
export GEOSERVER_PASSWORD="geoserver"

Windows PowerShell:

$env:GEOSERVER_URL="http://localhost:8080/geoserver"
$env:GEOSERVER_USER="admin"
$env:GEOSERVER_PASSWORD="geoserver"

1. Start the server:

If you are going to use Claude desktop you don't need this step. For cursor or your own custom client you should run the following code.

Linux:

source .venv/bin/activate

geoserver-mcp

or

source .venv/bin/activate

geoserver-mcp --url http://localhost:8080/geoserver --user admin --password geoserver --debug

Windows PowerShell:

.\.venv\Scripts\activate
geoserver-mcp

or

.\.venv\Scripts\activate
geoserver-mcp --url http://localhost:8080/geoserver --user admin --password geoserver --debug

1. Configure Clients:

If you are using Claude Desktop, edit claude_desktop_config.json If you are using Cursor, Create .cursor/mcp.json

Windows:

{
  "mcpServers": {
    "geoserver-mcp": {
      "command": "C:\\path\\to\\geoserver-mcp\\.venv\\Scripts\\geoserver-mcp",
      "args": [
        "--url",
        "http://localhost:8080/geoserver",
        "--user",
        "admin",
        "--password",
        "geoserver"
      ]
    }
  }
}

Linux:

{
  "mcpServers": {
    "geoserver-mcp": {
      "command": "/path/to/geoserver-mcp/.venv/bin/geoserver-mcp",
      "args": [
        "--url",
        "http://localhost:8080/geoserver",
        "--user",
        "admin",
        "--password",
        "geoserver"
      ]
    }
  }
}

🛠️ Development installation

The development installation is designed for contributors and developers who want to modify the codebase. This method is suitable for:

• Developers contributing to the project
• Users who need to modify the source code
• Testing new features
• Debugging and development purposes

1. Install uv package manager.

pip install uv

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

uv venv --python=3.10

1. Install the package using pip:

uv pip install -e .

1. Configure GeoServer connection:

Linux/Mac:

export GEOSERVER_URL="http://localhost:8080/geoserver"
export GEOSERVER_USER="admin"
export GEOSERVER_PASSWORD="geoserver"

Windows PowerShell:

$env:GEOSERVER_URL="http://localhost:8080/geoserver"
$env:GEOSERVER_USER="admin"
$env:GEOSERVER_PASSWORD="geoserver"

1. Start the server:

If you are going to use Claude desktop you don't need this step. For cursor or your own custom client you should run the following code.

Linux:

source .venv/bin/activate

geoserver-mcp

or

source .venv/bin/activate

geoserver-mcp --url http://localhost:8080/geoserver --user admin --password geoserver --debug

Windows PowerShell:

.\.venv\Scripts\activate
geoserver-mcp

or

.\.venv\Scripts\activate
geoserver-mcp --url http://localhost:8080/geoserver --user admin --password geoserver --debug

1. Configure Clients:

If you are using Claude Desktop, edit claude_desktop_config.json If you are using Cursor, Create .cursor/mcp.json

Windows:

{
  "mcpServers": {
    "geoserver-mcp": {
      "command": "C:\\path\\to\\geoserver-mcp\\.venv\\Scripts\\geoserver-mcp",
      "args": [
        "--url",
        "http://localhost:8080/geoserver",
        "--user",
        "admin",
        "--password",
        "geoserver"
      ]
    }
  }
}

Linux:

{
  "mcpServers": {
    "geoserver-mcp": {
      "command": "/path/to/geoserver-mcp/.venv/bin/geoserver-mcp",
      "args": [
        "--url",
        "http://localhost:8080/geoserver",
        "--user",
        "admin",
        "--password",
        "geoserver"
      ]
    }
  }
}

File Storage and --storage Usage

GeoServer MCP server supports an optional --storage flag to specify a base directory for all file read/write operations, such as uploading shapefiles, GeoTIFFs, or exporting results.

Overview

• The --storage flag sets the root folder for file operations from all data-related tools.
• You may supply relative paths (relative to storage root) or absolute paths (bypassing the storage root) as arguments to relevant tools.
• If --storage is not set, paths are resolved as provided by the user (relative to working directory or absolute).

CLI Example

python -m geoserver_mcp.main --storage D:/my/data/dir

This sets D:/my/data/dir as the base path for all files.

Example tool call in Python:

# Will read from D:/my/data/dir/roads.zip if --storage is set to D:/my/data/dir
create_shp_datastore('workspace', 'datastore_name', 'roads.zip')

Absolute paths (e.g. 'C:/input/other.shp') are always used as-is.

When Running in Docker

If using Docker, ensure the storage directory is mounted as a volume, e.g.:

docker run -v D:/my/data:/opt/data ...

Then launch the server with:

python -m geoserver_mcp.main --storage /opt/data

Best Practices

• Use relative paths when interacting with the API/tools as it keeps your setup portable.
• For remote or container deployment, always ensure your file data is accessible within the container (use Docker volumes if needed).
• Check tool docstrings for which arguments use the storage system.

The --storage system streamlines file management for all users and makes deployment much more flexible!

🛠️ Available Tools

This section details all the available tools and resources exposed by the GeoServer MCP server. These tools allow LLMs to interact with GeoServer's REST API for comprehensive geospatial data management.

🌍 Resource Endpoints

Resource endpoints provide direct access to GeoServer resources via a URI pattern.

📦 Workspace Management

📁 Datastore & Coveragestore Management

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