indxr vs unity-mcp
indxr: indxr gives AI coding agents a structural map of codebases, reducing token costs by ~5x compared to reading full files. It supports 27 languages, provides a 22-tool MCP server for live queries, and features incremental caching, git structural diffing, and dependency graphs. Setup is one-command with `indxr init` for popular AI coding agents.; unity-mcp: MCP for Unity integrates AI assistants like Claude and VS Code Copilot with the Unity Editor using the Model Context Protocol. This allows developers to use Large Language Models to manage assets, control scenes, edit scripts, and automate various tasks within Unity, streamlining game development workflows.
TL;DR
AI coding agents understanding a codebase without full file reads
- You develop games in Unity and want AI assistants (Claude, Cursor) to manage assets, inspect hierarchy, edit C# scripts, and run Editor commands via MCP.
- You want to automate scene setup, prefab creation, and repetitive Unity Editor tasks using natural language.
- You use Unreal Engine or Godot; unity-mcp connects strictly to the Unity Editor.
- You only write gameplay C# logic outside of Unity and do not need Editor-level RPC integration.
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