QGIS MCP Server

Overview

The QGISMCP server bridges the powerful geographic information system (QGIS) with Claude AI through the Model Context Protocol. By exposing QGIS’s full suite of project, layer, and processing capabilities to an AI assistant, it eliminates the need for manual interaction with the QGIS interface. Developers can now write natural‑language prompts that create projects, load datasets, run spatial analyses, and even execute arbitrary Python code directly inside QGIS—all orchestrated by Claude.

At its core, the server provides a socket‑based bridge between Claude and a QGIS plugin. The plugin launches a lightweight TCP server that listens for MCP commands, while the standalone Python process implements the protocol and forwards those commands to QGIS. This two‑tier architecture keeps the heavy lifting inside QGIS, where all spatial data and processing tools reside, while allowing Claude to issue high‑level instructions without exposing the entire QGIS UI.

Key capabilities include:

• Project lifecycle management – create, load, and save QGIS projects on demand.
• Layer manipulation – add or remove vector and raster layers, adjust symbology, and query layer metadata.
• Processing toolbox integration – invoke any algorithm from the Processing Toolbox, passing parameters and retrieving results.
• Python execution – run arbitrary Python scripts within QGIS’s environment, enabling custom workflows or data transformations.

These features make the server invaluable for geospatial developers who want to prototype or automate complex workflows. For example, a data scientist could ask Claude to “load the latest census shapefile, buffer it by 1 km, and export a GeoJSON” and the entire sequence would happen automatically. Similarly, an analyst could request “run a network analysis to find shortest routes between all parks and public schools” and receive both the results and visualizations without leaving the chat.

Integration with AI workflows is seamless: once the MCP server is running in QGIS and registered in Claude’s desktop configuration, a simple hammer icon appears in the tool palette. Each tool corresponds to an MCP command, and developers can extend the set by adding new plugin actions or custom Python functions. The server’s two‑way communication ensures that Claude receives status updates, error messages, and result data in real time, allowing for interactive debugging and iterative development.

In summary, QGISMCP turns Claude into a full‑blown geospatial analyst, enabling rapid prototyping, automation, and collaborative exploration of spatial data—all through conversational AI.