Ahk MCP Server

Ahk MCP – Bridging AI Assistants and Windows Automation

The Ahk MCP server solves a common pain point for developers building AI‑powered workflows on Windows: the lack of a unified, programmable interface to native desktop automation. Traditional tools for controlling windows, simulating user input, or extracting UI information are scattered across different APIs and languages. Ahk MCP consolidates these capabilities into a single MCP service that exposes 33 discrete tools, all built on top of AutoHotkey’s mature automation engine. By doing so, it gives Claude or any other MCP‑compatible model instant access to the full breadth of Windows UI manipulation without requiring the user to write or maintain scripts.

At its core, the server offers four families of actions that are indispensable for any desktop automation scenario. First, it can enumerate and interrogate windows—retrieving titles, class names, positions, and even the text content of controls that are not exposed through standard APIs. Second, it provides fine‑grained input simulation: typing, clicking, scrolling, and keyboard shortcuts can be orchestrated with millisecond precision. Third, it supports visual‑based interactions through screen capture and OCR via EasyOCR, allowing the model to read text that is rendered as images or canvas elements. Fourth, it delivers monitor‑level context, enabling the model to understand which windows reside on primary or secondary displays and adjust actions accordingly. These capabilities are delivered through a consistent tool interface, making them easy to invoke from any MCP‑enabled prompt.

The value for developers lies in the ability to compose complex, stateful workflows entirely within an AI assistant. For example, a model can be instructed to “open the Settings app, navigate to the Display section, and increase brightness” by chaining together window enumeration, click simulation, and OCR verification. Because each tool is exposed as a stateless operation, developers can write prompts that describe high‑level intent while the server handles low‑level execution details. This reduces boilerplate code, eliminates platform inconsistencies, and speeds up prototyping of automation scripts.

Real‑world use cases span from accessibility solutions—automating repetitive tasks for users with limited input devices—to testing and quality assurance, where a model can simulate user interactions across multiple monitors. IT administrators might use it to deploy configuration changes, while content creators could automate publishing workflows that involve multiple desktop applications. The server’s tight integration with the Python MCP SDK and FastMCP means it can be added to existing Claude Desktop or other AI toolchains with minimal friction, enabling instant desktop control without exposing the underlying AutoHotkey scripts to end users.

What sets Ahk MCP apart is its blend of low‑level Windows control and high‑level AI orchestration. By leveraging AutoHotkey’s full feature set behind an MCP interface, it provides a powerful yet developer‑friendly bridge between AI models and the Windows desktop. This unique combination empowers developers to build sophisticated, end‑to‑end automation solutions that feel natural within conversational AI workflows.