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geoserver-mcp

MCP.Pizza Chef: mahdin75

GeoServer MCP Server is a Model Context Protocol server that integrates Large Language Models with the GeoServer REST API, enabling AI assistants to access, query, and manipulate geospatial data and services in real time. It facilitates seamless interaction between LLMs and geospatial infrastructure, supporting advanced geospatial workflows and automation.

Use This MCP server To

Query geospatial data via natural language requests Manage GeoServer workspaces and layers programmatically Automate geospatial data updates and publishing Integrate geospatial services into AI-driven workflows Enable AI assistants to visualize and analyze maps Fetch metadata and configuration from GeoServer instances Support multi-step geospatial data processing with LLMs

README

GeoServer MCP Server

A Model Context Protocol (MCP) server implementation that connects Large Language Models (LLMs) to the GeoServer REST API, enabling AI assistants to interact with geospatial data and services.

GeoServer MCP Server Logo

Alpha

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

GeoServer MCP Server 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
  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"
      ]
    }
  }
}

🛠️ 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:

  1. Fork the repository
  2. Create a feature branch (git checkout -b feature/AmazingFeature)
  3. Commit your changes (git commit -m 'Add some AmazingFeature')
  4. Push to the branch (git push origin feature/AmazingFeature)
  5. 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.

🔗 Related Projects

📞 Support

For support, please Open an issue

🏆 Badges

geoserver-mcp FAQ

How do I install the GeoServer MCP Server?
You can install it via Docker or pip; detailed instructions are available in the GitHub repository.
What GeoServer versions are supported?
The server supports GeoServer versions compatible with its REST API, typically recent stable releases; check the documentation for specifics.
Can I use this MCP server with any LLM provider?
Yes, it is provider-agnostic and works with OpenAI, Anthropic Claude, Google Gemini, and others.
Is the GeoServer MCP Server production-ready?
It is currently in alpha development; contributions and testing are encouraged before production use.
How does the MCP server handle authentication with GeoServer?
It supports standard GeoServer REST API authentication methods, including basic auth and token-based schemes.
Can I extend the GeoServer MCP Server functionality?
Yes, it is open source and designed for extensibility; developers can contribute new features or integrations.
Does the server support real-time updates from GeoServer?
It can query and interact with GeoServer in real time, but push notifications depend on GeoServer capabilities.
What programming languages can interact with this MCP server?
Any language that can communicate over HTTP with the MCP client can interact with the server.