Godot MCP

The Godot MCP server bridges the gap between AI assistants and game development workflows by exposing a Model Context Protocol interface that talks directly to Godot projects. Developers often need AI tools to query scene hierarchies, manipulate nodes, or retrieve script metadata while working in a live editor. This server solves that friction by providing a lightweight, language‑agnostic API that can be queried from any Claude or similar assistant without custom SDKs.

At its core, the server offers a set of resource‑oriented endpoints that mirror Godot’s scene graph. An AI can request the list of nodes in a given scene, fetch a node’s properties or attached scripts, and even modify values on the fly. The service is built with Node.js and TypeScript, ensuring robust type safety while keeping runtime overhead minimal. It automatically watches the Godot project directory for changes, so the context presented to the assistant is always up‑to‑date. This live connectivity eliminates the need for manual export or JSON dumps, allowing developers to ask questions like “Show me all enemies in the current level” or “Increase the speed of the player character by 20%.”

Key capabilities include:

• Scene inspection – retrieve full node trees, including nested children and groups.
• Property manipulation – read or write any exported variable or built‑in property of a node.
• Script introspection – list functions, signals, and documentation strings from attached GDScript or C# scripts.
• Contextual prompts – the server can supply custom prompts that embed project‑specific information, helping the assistant generate more accurate code snippets.
• Sampling controls – fine‑grained limits on token usage and response length keep interactions efficient.

Real‑world use cases span from rapid prototyping—where an AI can auto‑generate a collision shape or adjust physics parameters—to debugging sessions that require inspecting runtime values without leaving the editor. Game designers can ask for “a list of all collectible items in scene X” and receive an instant, structured answer. QA teams can query the state of AI agents or environmental triggers during automated test runs.

Integration into existing AI workflows is straightforward: the MCP server exposes a standard HTTP interface, so any tool that can send JSON requests (e.g., Claude’s tool‑use framework) can invoke it. Once connected, developers benefit from a single source of truth for project data, reducing context switching and enabling AI‑powered code completion, documentation generation, and automated refactoring directly inside the Godot ecosystem.