MCP‑idb – Bridging AI Assistants to iOS Device Management

MCP‑idb is a Model Context Protocol (MCP) server that connects AI assistants to Facebook’s iOS Development Bridge (idb). By exposing idb’s rich set of device‑management and test‑execution commands over MCP, the server allows conversational agents to control physical or virtual iOS devices as if they were native tools. This eliminates the need for manual scripting or command‑line interactions, enabling AI workflows to trigger device actions directly from natural language queries.

The core problem MCP‑idb solves is the disconnect between AI assistants and mobile testing infrastructure. Developers routinely need to install apps, run automated tests, capture screenshots, or simulate user interactions on iOS devices. Traditionally this requires a developer to run idb commands locally, manage device connections, and parse output. MCP‑idb abstracts these details behind a standardized protocol: the assistant sends a request like “run UITest on device X”, and the server translates it into the appropriate idb call, returning results in a structured format. This seamless integration reduces context switching and speeds up iteration cycles.

Key capabilities of MCP‑idb include:

• Device discovery and connection – list connected iOS devices, verify trust status, and ensure developer mode is enabled.
• Application lifecycle management – install or uninstall apps by bundle identifier, reset app data, and query installed applications.
• Automated test execution – launch Xcode UI tests or custom scripts, capture logs, and report pass/fail status.
• Screenshot and recording – take screenshots or record screen sessions for visual regression testing.
• Simulated user interactions – perform taps, swipes, and other gestures programmatically.

Real‑world scenarios that benefit from MCP‑idb are plentiful. QA teams can embed the server in CI pipelines, letting an AI assistant trigger a full test suite on multiple devices and aggregate results. Mobile developers can prototype UI flows by describing desired interactions to the assistant, which then translates them into idb gestures. Test engineers can quickly generate screenshots for documentation or regression comparison without leaving the chat interface. Because MCP‑idb operates over a lightweight, stateless protocol, it scales from local development machines to cloud‑based device farms.

Integrating MCP‑idb into an AI workflow is straightforward: add the server to your , and expose its command set as a tool in the assistant’s prompt. The assistant can then invoke idb operations via natural language, and receive structured JSON responses that can be fed into subsequent steps of a larger automation script. This tight coupling between conversational AI and device tooling unlocks new possibilities for rapid prototyping, automated testing, and continuous delivery in the iOS ecosystem.