How to Automate GIS Tasks with QGIS and AI: A Step-by-Step Guide

Artificial intelligence (AI) is generating significant buzz these days. A variety of models have emerged, starting with ChatGPT, followed by Gemini, DeepSeek, Claude, and many others. Each day, I witness AI’s growing influence in shaping our world, answering questions, assisting with coding, generating images and videos, and powering countless other applications. As a GIS professional, I naturally want AI to support us in tackling GIS tasks. In a previous discussion, I explored how to make a map with ChatGPT. However, I believe AI offers far more to GIS professionals than just map creation. Beyond generating maps based on provided data, AI can enhance our ability to perform complex GIS analysis and streamline workflows.

In this post, I’d like to explore how AI can assist us in automating GIS tasks, from creating a new project and adding data to selecting features, performing processing, and exporting results. For this guide, I’ll use a protocol called the Model Context Protocol (MCP) to enable communication between QGIS and AI. MCP is an open standard that connects AI models like Claude or DeepSeek to external applications, allowing them to exchange data and execute commands seamlessly. By leveraging MCP, we can harness AI’s capabilities to streamline workflows and enhance productivity in QGIS, making complex tasks more efficient and accessible.

Prerequisites

Before we dive into the automation process, let’s ensure you have the necessary tools set up namely QGIS, Claude Dekstop, UV Package manager and of course Python.

QGIS 3.X

QGIS is the core GIS platform we’ll be automating. While the latest version (e.g., 3.34) works well, I’ve tested this setup on QGIS 3.26 Buenos Aires to ensure compatibility. It includes the Python console and PyQGIS API, which are essential for scripting and AI integration. If you don’t have QGIS installed yet, download it from qgis.org.

Claude Desktop

UV Package Manager

The uv package manager, developed by Astral, is a fast, modern alternative to pip for managing Python dependencies. It’s optional but highly recommended for installing MCP-related libraries efficiently. To install uv you can follow the instructions from this Github.

Python 3.10+

Python powers QGIS scripting, and we need version 3.10 or later for compatibility with modern tools and libraries.

Make sure you downloaded all the prerequisites before moving to the next step.

Installing QGIS MCP Plugin

The next step is to install the QGIS MCP Plugin. You can get the plugin from Github's jjsantos01/qgis_mcp or simply using git in command prompt or shell: git clone git@github.com:jjsantos01/qgis_mcp.git as shown in the figure 1.

Figure 1. Git Clone to get QGIS MCP Plugin

You will get a folder called qgis_mcp. Figure 2 shows the content of the folder.

Figure 2. QGIS MCP Folder

To install the qgis_mcp_plugin we need to copy the qgis_mcp_plugin folder into QGIS Active Profile Folder. You can access the active profile folder from QGIS in the Settings > User Profiles > Open Active Profile Folder as seen in the figure 3.

{
    "mcpServers": {
        "qgis": {
            "command": "uv",
            "args": [
                "--directory",
                "YOUR PARENT FOLDER/qgis_mcp/src/qgis_mcp",
                "run",
                "qgis_mcp_server.py"
            ]
        }

    }
}