GeoServer MCP Server

Version 0.4.0 (Alpha) 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

🔍 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:

🛠️ 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

Run geoserver-mcp:

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

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

Install uv package manager.

pip install uv

Create the Virtual Environment (Python 3.10+):

Linux/Mac:

uv venv --python=3.10

Windows PowerShell:

uv venv --python=3.10

Install the package using pip:

uv pip install geoserver-mcp

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"

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

source .venv/bin/activate

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

Windows PowerShell:

.\.venv\Scripts\activate
geoserver-mcp

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

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

Install uv package manager.

pip install uv

Create the Virtual Environment (Python 3.10+):

uv venv --python=3.10

Install the package using pip:

uv pip install -e .

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"

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

source .venv/bin/activate

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

Windows PowerShell:

.\.venv\Scripts\activate
geoserver-mcp

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

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"
      ]
    }
  }
}

🛠️ Available Tools

🛠️ Workspace and Layer Management

Tool	Description
`list_workspaces`	Get available workspaces
`create_workspace`	Create a new workspace
`get_layer_info`	Get detailed layer metadata
`list_layers`	List layers in a workspace
`create_layer`	Create a new layer
`delete_resource`	Remove resources

🛠️ Data Operations

Tool	Description
`query_features`	Execute CQL queries on vector data
`update_features`	Modify feature attributes
`delete_features`	Remove features based on criteria

🛠️ Visualization

Tool	Description
`generate_map`	Create styled map images
`create_style`	Define new SLD styles
`apply_style`	Apply existing styles to layers

🛠️ Client Development

If you're planning to develop your own client to interact with the GeoServer MCP server, you can find inspiration in the example client implementation at examples/client.py. This example demonstrates:

How to establish a connection with the MCP server
How to send requests and handle responses
Basic error handling and connection management
Example usage of various tools and operations

The example client serves as a good starting point for understanding the protocol and implementing your own client applications.

Also, here is the example usgage:

List Workspaces

Tool: list_workspaces
Parameters: {}
Response: ["default", "demo", "topp", "tiger", "sf"]

Get Layer Information

Tool: get_layer_info
Parameters: {
"workspace": "topp",
"layer": "states"
}

Query Features

Tool: query_features
Parameters: {
"workspace": "topp",
"layer": "states",
"filter": "PERSONS > 10000000",
"properties": ["STATE_NAME", "PERSONS"]
}

Generate Map

Tool: generate_map
Parameters: {
"layers": ["topp:states"],
"styles": ["population"],
"bbox": [-124.73, 24.96, -66.97, 49.37],
"width": 800,
"height": 600,
"format": "png"
}

🔮 Planned Features

Coverage and raster data management
Security and access control
Advanced styling capabilities
WPS processing operations
GeoWebCache integration

🤝 Contributing

We welcome contributions! Here's how you can help:

Fork the repository
Create a feature branch (git checkout -b feature/AmazingFeature)
Commit your changes (git commit -m 'Add some AmazingFeature')
Push to the branch (git push origin feature/AmazingFeature)
Open a Pull Request

Please ensure your PR description clearly describes the problem and solution. Include the relevant issue number if applicable.

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

Model Context Protocol - The core MCP implementation
GeoServer REST API - Official GeoServer REST documentation
GeoServer REST Python Client - Python client for GeoServer REST API

📞 Support

For support, please Open an issue

🏆 Badges

Install Server

HTTP connection URL

security – no known vulnerabilities

license - permissive license

quality - confirmed to work

How are these scores calculated?

hybrid server

The server is able to function both locally and remotely, depending on the configuration or use case.

Tools

View all tools

A Model Context Protocol server that connects Large Language Models to the GeoServer REST API, enabling AI assistants to query and manipulate geospatial data through natural language.

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Reddit Discussion about this server

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