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Geoserver MCP

by mahdin75

Connects MCP-compatible AI clients to GeoServer for REST administration, spatial queries, OGC services, and map generation.

Install Geoserver MCP

Pick your client, then add it in one click or paste the config.

Streamable HTTP (Remote)
Server URL
https://mcp.so/server/Geoserver%20MCP%20Server/mahdin75

Remote servers are added in the app, not the config file: Customize → Connectors → Add custom connector, then paste this URL.

Overview

mahdin75/geoserver-mcp MCP server connects MCP-compatible AI clients to a running GeoServer instance through its REST API. It exposes operations for workspaces, stores, layers, styles, users, feature types, and service configuration, along with spatial queries and map visualization capabilities. The Python package runs locally through pip, Docker, or a client configuration, while a separate GeoServer extension targets GeoServer 2.28.x and provides an MCP endpoint. Reach for it when an agent needs to inspect or manage GeoServer resources rather than only read geospatial files.

Use cases

  • Inspect GeoServer workspaces and layers
  • Manage datastores, coveragestores, and styles
  • Run spatial queries on vector data
  • Generate map visualizations
  • Administer GeoServer users and groups

Key features

  • GeoServer REST API access over MCP
  • Workspace, layer, and layer group management
  • Datastore and coveragestore management
  • Spatial queries on vector data
  • WMS and WFS access
  • Map visualization generation

Security & health

What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.

ActiveLast checked 1d ago

Recent health check succeeded.

20/20 checks healthy over the last 79d

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 8/26/2026 via OSV.dev · https://mcp.so/server/Geoserver%20MCP%20Server/mahdin75 (npm)

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars95Stargazers on the source repository.
Last commit2mo agoMost recent push to the default branch.
Directory activity4 viewsConfig copies, upvotes, and views on AllMCPs.

How Geoserver MCP works

What mahdin75/geoserver-mcp MCP server does

mahdin75/geoserver-mcp MCP server gives an MCP-compatible AI client access to a GeoServer installation through the GeoServer REST API. It is intended for environments where an agent needs to inspect or modify published geospatial resources, perform spatial queries, or work with map and OGC service configuration.

The documented feature set covers workspace, datastore, coveragestore, layer, layer group, user, user group, feature type, attribute, and style management. It also includes system and service operations, style XML utilities, map visualization, and access to WMS and WFS services.

How it works

The primary deployment is a Python MCP process running separately from GeoServer. The process communicates with the MCP client and sends requests to the configured GeoServer REST API. A running GeoServer instance with REST enabled is therefore required, as is Python 3.10 or newer when using the Python installation.

The repository also describes a separate GeoServer extension. That artifact is installed inside GeoServer and exposes a remote MCP endpoint at /geoserver/mcp; it does not require a Python sidecar and is aimed at GeoServer 2.28.x. The extension and Python package are separate deployment options, not interchangeable installation steps.

Setup and configuration

For the Python package, install geoserver-mcp into a Python 3.10+ environment, then start the geoserver-mcp executable. The server accepts the GeoServer connection through GEOSERVER_URL, GEOSERVER_USER, and GEOSERVER_PASSWORD, or through corresponding command-line options such as --url, --user, and --password. A debug option is also documented.

Docker is another documented route. The image is mahdin75/geoserver-mcp; client configurations pass the GeoServer URL and credentials into the container as environment variables. Claude Desktop and Cursor configuration examples are included. Smithery installation is also documented for Claude Desktop, but it is an installer route rather than the project’s own server command.

Tools and capabilities

The README groups the available operations into these areas:

  • List and inspect resource endpoints
  • Manage workspaces
  • Manage datastores and coveragestores
  • Create or modify layers and layer groups
  • Manage users and user groups
  • Work with feature types and attributes
  • Manage styles and use style XML utilities
  • Perform system and service operations
  • Run spatial queries on vector data
  • Retrieve layer information and generate map visualizations

Limitations and notes

The project labels version 0.5.0 as beta and under active development. It requires access to a live GeoServer REST API; the MCP package is not described as a standalone geospatial database or file-processing server. Credentials must be supplied for the configured GeoServer connection, and the example values in the README should be replaced with credentials appropriate to the target installation.

The Python server and GeoServer extension should be evaluated separately.

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Frequently Asked Questions about Geoserver MCP

Install the Python package `geoserver-mcp` in a Python 3.10+ environment, run the documented Docker image, or use the Smithery installation route for Claude Desktop.

The documented connection variables are `GEOSERVER_URL`, `GEOSERVER_USER`, and `GEOSERVER_PASSWORD`.

Yes. The README provides Claude Desktop configuration examples and documents Smithery installation for Claude.

Yes. The README includes a Cursor `.cursor/mcp.json` configuration example.

Its documented areas include workspaces, datastores, coveragestores, layers, layer groups, users, groups, feature types, attributes, styles, system and service operations, spatial queries, and map generation.

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