GeoServer MCP Server
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"
Installation
From PyPI
pip install geoservercloud-mcp
Or use uvx to run without installing (requires uv):
curl -LsSf https://astral.sh/uv/install.sh | sh
uvx geoservercloud-mcp
From MCP Registry
This server is published to the MCP Registry as:
io.github.ronitjadhav/geoservercloud-mcp
Connecting to AI Clients
VS Code / Cursor
Add to your MCP configuration (.vscode/mcp.json):
{
"servers": {
"geoserver": {
"command": "uvx",
"args": ["geoservercloud-mcp"],
"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": "uvx",
"args": ["geoservercloud-mcp"],
"env": {
"GEOSERVER_URL": "http://localhost:8080/geoserver",
"GEOSERVER_USER": "admin",
"GEOSERVER_PASSWORD": "geoserver"
}
}
}
}
Restart Claude Desktop after saving the configuration.
Claude Code
Add the server with the claude mcp add command:
claude mcp add geoserver \
--env GEOSERVER_URL=http://localhost:8080/geoserver \
--env GEOSERVER_USER=admin \
--env GEOSERVER_PASSWORD=geoserver \
-- uvx geoservercloud-mcp
This adds it at the default local (per-project) scope. Use --scope user to make
it available in all your projects, or --scope project to write it to a shared
.mcp.json committed in the repo. Omit the --env flags to configure the connection
at runtime instead (the AI will ask for the URL and credentials).
Manage it with:
claude mcp list
claude mcp get geoserver
claude mcp remove geoserver
Dynamic Configuration (No Hardcoded Credentials)
You can omit the env section entirely. The AI will ask you for the GeoServer URL, username, and password at runtime:
{
"mcpServers": {
"geoserver": {
"command": "uvx",
"args": ["geoservercloud-mcp"]
}
}
}
Environment Variables
GEOSERVER_URL | http://localhost:8080/geoserver | GeoServer base URL |
GEOSERVER_USER | admin | GeoServer username |
GEOSERVER_PASSWORD | geoserver | GeoServer password |
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/
Development
For local development, testing, and publishing, see the Developer Guide.