An MCP server that wraps the [python-geoservercloud](https://github.com/camptocamp/python-geoservercloud) library, exposing 80+ GeoServer operations as natural-language tools for AI assistants like Claude, VS Code Copilot, and other MCP-compatible clients.
Once connected, you can just ask:
- _"List all workspaces in GeoServer"_
- _"Create a new workspace called `test_data`"_
- _"Publish the `roads` table from my PostGIS database"_
## Quick start (Claude Code)
One command — no manual install, `uvx` fetches and runs the server for you.
**Simplest — no credentials up front:**
```bash
claude mcp add geoserver -- uvx geoservercloud-mcp
```
The AI will ask you for the GeoServer URL, username, and password when it first
needs them. Great for trying it out or switching between servers.
**Or set the connection up front:**
```bash
claude mcp add geoserver \
--env GEOSERVER_URL=http://localhost:8080/geoserver \
--env GEOSERVER_USER=admin \
--env GEOSERVER_PASSWORD=geoserver \
-- uvx geoservercloud-mcp
```
That's it — start Claude Code and ask it to list your workspaces to confirm
it's connected.
Manage it later with `claude mcp list`, `claude mcp get geoserver`, or
`claude mcp remove geoserver`. Add `--scope user` to the add command to make it
available in every project instead of just this one.
---
## Other clients
Claude Desktop
Add this to your config file, then restart Claude Desktop:
- **macOS:** `~/Library/Application Support/Claude/claude_desktop_config.json`
- **Linux:** `~/.config/Claude/claude_desktop_config.json`
```json
{
"mcpServers": {
"geoserver": {
"command": "uvx",
"args": ["geoservercloud-mcp"],
"env": {
"GEOSERVER_URL": "http://localhost:8080/geoserver",
"GEOSERVER_USER": "admin",
"GEOSERVER_PASSWORD": "geoserver"
}
}
}
}
```
VS Code / Cursor
Add this to `.vscode/mcp.json`:
```json
{
"servers": {
"geoserver": {
"command": "uvx",
"args": ["geoservercloud-mcp"],
"env": {
"GEOSERVER_URL": "http://localhost:8080/geoserver",
"GEOSERVER_USER": "admin",
"GEOSERVER_PASSWORD": "geoserver"
}
}
}
}
```
Install manually (pip / uvx)
```bash
# with pip
pip install geoservercloud-mcp
geoservercloud-mcp
# or run without installing (requires uv: https://docs.astral.sh/uv/)
uvx geoservercloud-mcp
```
Published to the [MCP Registry](https://registry.modelcontextprotocol.io) as
`io.github.ronitjadhav/geoservercloud-mcp`.
---
## Environment variables
| Variable | Default | Description |
| -------------------- | --------------------------------- | ------------------ |
| `GEOSERVER_URL` | `http://localhost:8080/geoserver` | GeoServer base URL |
| `GEOSERVER_USER` | `admin` | GeoServer username |
| `GEOSERVER_PASSWORD` | `geoserver` | GeoServer password |
All three are optional — if you skip them, you can configure the connection at
runtime by asking the AI.
---
## Development
Want to run it from source or contribute?
```bash
git clone https://github.com/ronitjadhav/geoservercloud-mcp.git
cd geoservercloud-mcp
poetry install # set up the environment
poetry run pytest # run the tests
poetry run geoservercloud-mcp # run the server (stdio)
```
Need a GeoServer to test against? `cd docker && docker compose up -d` spins up
GeoServer + PostGIS + the MCP server.
For the full workflow — adding new tools, linting, releasing, and how publishing
works — see the **[Developer Guide](docs/DEVELOPER.md)**.
---
## Python library
This server is built on the **python-geoservercloud** library. For programmatic
access without MCP:
```python
from geoservercloud import GeoServerCloud
geoserver = GeoServerCloud(
url="http://localhost:8080/geoserver",
user="admin",
password="geoserver",
)
geoserver.create_workspace("my_workspace")
```
Full library docs: