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GIS Toolkit MCP

by celikn
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Python
Hybrid

GIS Toolkit MCP

A standalone Model Context Protocol server exposing common file-level GIS operations — buffer, clip, reproject, overlay, spatial join, zonal statistics, nearest neighbor, dissolve, centroid, length/area fields. Built with FastMCP.

This package has no dependency on any other project. Any MCP client can use it as long as it can reach the server over HTTP and share a filesystem with it (see "Data access" below).

Why file-level, not geometry-level

Most GIS MCP servers expose single-geometry operations (e.g. buffer(geometry: str, distance)). That's the wrong granularity for "process this whole dataset" tasks — buffering a 1,000-feature shapefile that way means 1,000 separate tool calls. Every tool here instead takes a file path in, a file path out, and processes the whole dataset in one call.

Related MCP server: Eddie MCP Server

Tools

Tool

What it does

buffer_file

Buffer every feature by a distance in meters (auto-projects geographic CRS)

clip_file

Clip a vector or raster file to a vector mask's boundary

reproject_file

Reproject a vector or raster file to a target CRS

overlay_file

Union / intersection / difference / symmetric_difference of two vector files

spatial_join_file

Spatial join two vector files by a predicate (intersects, contains, ...)

dissolve_file

Merge features sharing the same value in a field

centroid_file

Replace geometries with their centroids, keeping attributes

zonal_statistics_file

Per-zone raster statistic (min/max/mean/sum/std/count/median) as a new field

nearest_neighbor_file

k-nearest-neighbor distance + index from one file to another

add_length_area_field

Add a length (lines) or area (polygons) field, computed in meters

select_by_attribute_file

Keep only features where a field compares true against a value (==, !=, >, <, contains); supports string-encoded dict fields like OSM tags via nested_key

upload_file

Save base64-encoded content into the server's data directory, for clients with no shared filesystem access

download_file

Read back a file's content as base64, e.g. to retrieve another tool's output

Running it

pip install -r requirements.txt
python3 server.py

Or via Docker:

docker build -t gis-toolkit-mcp .
docker run -p 9020:9020 -v /path/to/your/data:/data -e GIS_TOOLKIT_DATA_DIR=/data gis-toolkit-mcp

The server listens on http://0.0.0.0:9020/mcp by default (Streamable HTTP transport).

Configuration

Env var

Default

Meaning

GIS_TOOLKIT_DATA_DIR

current working directory

Base directory relative tool paths are resolved against. Absolute paths pass through unchanged.

GIS_TOOLKIT_TRANSPORT

streamable-http

streamable-http, sse, or stdio

GIS_TOOLKIT_PORT

9020

Port for HTTP-based transports

Data access

Every tool takes plain file paths (input and output) and reads/writes them directly. If your client shares a filesystem with the server (e.g. a shared Docker volume, or both running on the same host), just mount your data directory and point GIS_TOOLKIT_DATA_DIR (or pass absolute paths) accordingly — no code changes needed.

If your client does not share a filesystem with the server (e.g. a remote user calling a publicly hosted instance from their own machine), there are two ways to get data in and out:

  • MCP tools: upload_file takes base64 content and returns a path to use as another tool's input_path; download_file reads a path back out as base64. Good for an MCP client or an LLM driving the tools programmatically.

  • Plain HTTP (for a human, or a chat UI's browser — base64 in a chat message is unwieldy): GET /upload serves a small HTML form to pick and submit a file directly; GET /files/<path> streams a file back with Content-Disposition: attachment, so pasting that URL as a link gives a real, clickable download in any browser.

Both paths are restricted to GIS_TOOLKIT_DATA_DIR — they refuse to read/write outside it. Note the base64 tools return one file at a time, so prefer single-file output formats (.geojson, .gpkg) over multi-file ones (.shp + its sidecars) when a remote client needs to retrieve the result.

Connecting a client

Any MCP client that supports Streamable HTTP can connect directly to http://<host>:9020/mcp. For example, in a librechat.yaml:

mcpServers:
  gis-toolkit:
    type: streamable-http
    url: http://<host>:9020/mcp

This server cannot be deployed

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Maintenance

ActivityMaintained
ResponsivenessNo issues

Resources

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