GameDevBench MCP

GameDevBench MCP

Enables LLM agents to capture screenshots and visualize runtime behavior within the Godot game engine for game development benchmarking. It utilizes AppleScript to provide display capture functionality for agents running on macOS.

Category
Visit Server

README

GameDevBench

A benchmark suite for evaluating LLM agents on game development tasks.

Paper: GameDevBench: A Comprehensive Benchmark for Game Development

Overview

GameDevBench contains 132 game development tasks to evaluate LLM agents' ability to complete game development problems in the Godot game engine.

Installation

Prerequisites

  1. Godot 4.x - Download and install from godotengine.org

    • Ensure godot is available in your PATH, or set GODOT_EXEC_PATH environment variable
  2. Python 3.10+ - Required for all agents

    • Python 3.12+ - Required for OpenHands agent

Install Agents

Install the agent(s) you want to use:

Setup Tasks

Before running the benchmark, unzip the tasks folder:

unzip tasks.zip

Note: The tasks are distributed as a zip file to prevent accidental data leakage.

Configuration

Environment Variables

You can use the built-in plans for claude-code, codex, and gemini-cli, or provide API keys directly. For OpenHands you must provide your own API keys. See .env.example for a complete list of optional environment variables.

Usage

Running the Benchmark

uv run python gamedevbench/src/benchmark_runner.py \
  --agent AGENT \
  --model MODEL \
  run --task-list tasks.yaml

Available Agents

  • claude-code - Anthropic's Claude Code CLI
  • codex - OpenAI Codex
  • gemini-cli - Google Gemini CLI
  • openhands - OpenHands (requires Python 3.12+)

Command-Line Options

  • --agent AGENT - Agent to use (required)
  • --model MODEL - Model name (e.g., claude-sonnet-4.5-20250929)
  • --enable-mcp - Enable MCP (Model Context Protocol) server for supported agents
    • Provides screenshot capabilities to the agent
    • Note: MCP server requires macOS (see limitations below)
  • --use-runtime-video - Enable runtime video mode
    • Appends Godot runtime instructions to prompts
    • Helps agents understand how to run and test their changes
  • --skip-display - Skip tasks that require display
  • run --task-list FILE - Run tasks from YAML file (e.g., tasks.yaml)

Platform Limitations

macOS-only Features:

  • MCP server screenshot functionality (--enable-mcp) currently only works on macOS
    • Uses AppleScript for display capture
    • Requires setting GODOT_SCREENSHOT_DISPLAY environment variable to correct display number

Results

Benchmark results are saved to results/ directory with the following information:

  • Task success/failure status
  • Token usage and costs
  • Execution time
  • Validation results

Citation

@misc{chi2026gamedevbenchevaluatingagenticcapabilities,
      title={GameDevBench: Evaluating Agentic Capabilities Through Game Development},
      author={Wayne Chi and Yixiong Fang and Arnav Yayavaram and Siddharth Yayavaram and Seth Karten and Qiuhong Anna Wei and Runkun Chen and Alexander Wang and Valerie Chen and Ameet Talwalkar and Chris Donahue},
      year={2026},
      eprint={2602.11103},
      archivePrefix={arXiv},
      primaryClass={cs.AI},
      url={https://arxiv.org/abs/2602.11103},
}

License

gamedevbench-bp

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured