geoservercloud-mcp 0.1.4

MCP (Model Context Protocol) server for GeoServer - enables AI assistants to manage GeoServer workspaces, datastores, layers, and styles through natural language

GeoServer MCP Server

mcp-name: io.github.ronitjadhav/geoservercloud-mcp

A Model Context Protocol (MCP) server that exposes GeoServer REST API functionality for natural language interaction through AI assistants like Claude, VS Code Copilot, and other MCP-compatible clients.

About

This MCP server wraps the python-geoservercloud library, exposing 80+ GeoServer operations as MCP tools. This enables AI assistants to manage GeoServer workspaces, datastores, layers, styles, and more through natural language commands.

Example Interactions

Once connected, you can ask your AI assistant things like:

• "List all workspaces in GeoServer"
• "Create a new workspace called 'test_data'"
• "What layers are available in the 'topp' workspace?"
• "Create a PostGIS datastore connection"

---

Quick Start

Option 1: Full Local Development Stack

Start the MCP server with a local GeoServer and PostGIS:

cd mcp
docker compose up -d

This starts:

• geoservercloud-mcp: The MCP server on port 8000
• geoserver: GeoServer instance on port 8080
• postgis: PostGIS database on port 5433

Option 2: MCP Server Only (Connect to External GeoServer)

If you have an existing GeoServer:

cd mcp
GEOSERVER_URL=http://your-geoserver:8080/geoserver \
GEOSERVER_USER=admin \
GEOSERVER_PASSWORD=your-password \
docker compose up -d geoservercloud-mcp

---

Connecting to AI Clients

VS Code / Cursor

1. Open Command Palette → "MCP: Add Server"
2. Select "Command (stdio)"
3. Enter command: poetry run geoservercloud-mcp
4. Enter server ID: geoserver

VS Code will create an MCP configuration file. Update it with the working directory and environment variables:

{
  "servers": {
    "geoserver": {
      "type": "stdio",
      "command": "poetry",
      "args": ["run", "geoservercloud-mcp"],
      "cwd": "/path/to/python-geoservercloud",
      "env": {
        "GEOSERVER_URL": "http://localhost:8080/geoserver",
        "GEOSERVER_USER": "admin",
        "GEOSERVER_PASSWORD": "geoserver"
      }
    }
  }
}

Claude Desktop

Add to your Claude Desktop config:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Linux: ~/.config/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "geoserver": {
      "command": "poetry",
      "args": ["run", "geoservercloud-mcp"],
      "cwd": "/path/to/python-geoservercloud",
      "env": {
        "GEOSERVER_URL": "http://localhost:8080/geoserver",
        "GEOSERVER_USER": "admin",
        "GEOSERVER_PASSWORD": "geoserver"
      }
    }
  }
}

Restart Claude Desktop after saving the configuration.

---

Testing with FastMCP Inspector

The MCP server includes a built-in inspector UI for debugging:

# From project root
poetry install
poetry run fastmcp dev geoservercloud/mcp/server.py

Open http://127.0.0.1:6274 in your browser to test individual tools.

---

Environment Variables

Variable	Default	Description
GEOSERVER_URL	http://localhost:8080/geoserver	GeoServer base URL
GEOSERVER_USER	admin	GeoServer username
GEOSERVER_PASSWORD	geoserver	GeoServer password

---

Docker Commands

# Start all services
cd mcp
docker compose up -d

# Stop services
docker compose down

# Stop and remove volumes (data)
docker compose down -v

# View logs
docker compose logs -f geoservercloud-mcp

---

Python Library

This MCP server is built on the python-geoservercloud library. For programmatic access without MCP, see the library documentation.

from geoservercloud import GeoServerCloud

geoserver = GeoServerCloud(
    url="http://localhost:8080/geoserver",
    user="admin",
    password="geoserver",
)
geoserver.create_workspace("my_workspace")

Full documentation: https://camptocamp.github.io/python-geoservercloud/