Geoserver MCP Server
G

Geoserver MCP Server

The GeoServer MCP Server is a server - side implementation of the Model Context Protocol (MCP) that connects large language models (LLMs) with the GeoServer REST API, enabling AI assistants to interact with geospatial data and services.
2.5 points
10.4K

What is the GeoServer MCP Server?

The GeoServer MCP Server is a middleware based on the Model Context Protocol (MCP), which serves as a bridge between AI assistants and GeoServer geospatial services. Through this server, non - technical users can use natural language to query and operate geospatial data without directly using complex GIS tools or APIs.

How to use the GeoServer MCP Server?

You can use it in three ways: 1) Quick deployment via Docker container; 2) Local installation and running via pip; 3) Installation in development mode. After installation, configure your AI client (such as Claude or Cursor) to connect to this server and start interacting.

Applicable scenarios

It is suitable for scenarios that require natural - language interaction to access geospatial data, such as urban planning consultations, environmental monitoring data analysis, commercial site selection analysis, etc., where geographical information support is needed but professional technical personnel are lacking.

Main features

Workspace management
Create, list, and delete GeoServer workspaces
Layer operations
Get layer information, create new layers, and manage existing layers
Spatial queries
Execute spatial queries and attribute filtering using natural language
Map visualization
Generate customized map image outputs
Advantages
Access geospatial data without GIS expertise
Simplify complex spatial operations through natural - language interaction
Support multiple installation methods to adapt to different environments
Seamlessly integrate with mainstream AI assistants
Limitations
Currently in the Alpha stage, and the functions are still being improved
Require pre - configuration of the GeoServer environment
Limited ability for complex spatial analysis
Performance depends on the underlying GeoServer configuration

How to use

Select an installation method
Choose Docker (recommended), pip installation, or development mode according to your needs
Configure the GeoServer connection
Set the GeoServer URL, username, and password
Start the MCP server
Run the server and ensure it is listening for requests
Configure the AI client
Configure the MCP server connection in your AI assistant (such as Claude or Cursor)

Usage examples

Query high - population states
Find all US states with a population of over 10 million
Create a thematic map
Generate a map of the United States colored by population density
Spatial analysis
Find all facilities within 10 kilometers of a certain point

Frequently Asked Questions

What version of GeoServer is required?
How to ensure connection security?
Which AI clients are supported?
How to optimize performance?

Related resources

Model Context Protocol
Core implementation of MCP
GeoServer REST documentation
Official GeoServer REST API documentation
GeoServer REST Python client
Python client library
Project issue tracking
Report issues or submit suggestions

Installation

Copy the following command to your Client for configuration
{
  "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"
      ]
    }
  }
}

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

{
  "mcpServers": {
    "geoserver-mcp": {
      "command": "/path/to/geoserver-mcp/.venv/bin/geoserver-mcp",
      "args": [
        "--url",
        "http://localhost:8080/geoserver",
        "--user",
        "admin",
        "--password",
        "geoserver"
      ]
    }
  }
}
Note: Your key is sensitive information, do not share it with anyone.

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