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editor-mcp-server

MCP.Pizza Chef: playcanvas

The editor-mcp-server is an MCP server designed to integrate AI automation capabilities directly into the PlayCanvas Editor. It facilitates real-time interaction between AI models and the PlayCanvas Editor environment, enabling automated workflows, content generation, and editing tasks within the game development platform. This server bridges the PlayCanvas Editor with LLMs, enhancing development efficiency and creative possibilities.

Use This MCP server To

Automate scene and asset editing in PlayCanvas Editor Generate game scripts and code snippets automatically Extract and summarize project data for reports Trigger editor actions via natural language commands Integrate AI-driven content creation into game development Manage PlayCanvas project files through AI workflows

README

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An MCP Server for automating the PlayCanvas Editor using an LLM.

Screenshot 2025-03-21 at 15 50 10

Important

At the moment, the MCP Server needs to be driven by Anthropic's Claude. Our experience shows that the free tier for Claude does not deliver a big enough chat context to operate the MCP Server reliably. Therefore, we strongly recommend subscribing to a Pro Claude account.

Available Tools

  • Entity
    • list_entities
    • create_entities
    • delete_entities
    • duplicate_entities
    • modify_entities
    • reparent_entity
    • add_components
    • remove_components
    • add_script_component_script
  • Asset
    • list_assets
    • create_assets
    • delete_assets
    • instantiate_template_assets
    • set_script_text
    • script_parse
    • set_material_diffuse
  • Scene
    • query_scene_settings
    • modify_scene_settings
  • Store
    • store_search
    • store_get
    • store_download

Installation

Run npm install to install all dependencies.

Install Chrome Extension

  1. Visit chrome://extensions/ and enable Developer mode
  2. Click Load unpacked and select the extensions folder
  3. Load the PlayCanvas Editor. The extension should be loaded.

Run MCP Server

The MCP Server can be driven by Cursor or Claude Desktop.

Tip

We have found Claude Desktop to be generally more reliable.

Claude Desktop
  1. Install Claude Desktop.
  2. Go to Claude > Settings.
  3. Select Developer and then Edit Config.
  4. This will open claude_desktop_config.json, your MCP Config JSON file.
Cursor
  1. Install Cursor.
  2. Select File > Preferences > Cursor Settings.
  3. Click + Add new global MCP server.
  4. This will open mcp.json, your MCP Config JSON file.

Tip

Also in Cursor Settings, select Features and scroll to the Chat section. Activate Enable auto-run mode to allow the LLM to run MCP tools without requiring constant authorization. You do this at your own risk (but we prefer it)!

Important

In Cursor, ensure you have Agent selected. Ask and Edit modes will not recognize the MCP Server.

MCP Config JSON File

This is how your config should look:

Windows

{
  "mcpServers": {
    "playcanvas": {
      "command": "cmd",
      "args": [
        "/c",
        "npx",
        "tsx",
        "C:\\path\\to\\mcp-editor\\src\\server.ts"
      ],
      "env": {
        "PORT": "52000"
      }
    }
  }
}

macOS

{
  "mcpServers": {
    "playcanvas": {
      "command": "npx",
      "args": [
        "tsx",
        "/path/to/mcp-editor/src/server.ts"
      ],
      "env": {
        "PORT": "52000"
      }
    }
  }
}

Connecting the Editor to the MCP Server

The PlayCanvas Editor does not connect to the MCP Server automatically. To connect:

  1. Activate a Chrome tab running the PlayCanvas Editor.
  2. Select the Extensions icon to the right of the address bar.
  3. Select PlayCanvas Editor MCP Extension to open the extension popup.
  4. Select CONNECT (the port number should match what is set in your MCP Config JSON File).

Note

You can currently only connect one instance of the PlayCanvas Editor to the MCP Server at any one time.

You should now be able to issue commands in Claude Desktop or Cursor.

editor-mcp-server FAQ

How do I install the editor-mcp-server?
Clone the repository from GitHub, follow the setup instructions in the README, and run the server in your PlayCanvas development environment.
Can the editor-mcp-server work with multiple LLM providers?
Yes, it supports integration with OpenAI, Anthropic Claude, and Google Gemini models for flexible AI interactions.
Is the editor-mcp-server secure for use in production?
The server follows MCP principles for secure, scoped, and observable model interactions, suitable for production with proper configuration.
How does the editor-mcp-server interact with the PlayCanvas Editor?
It exposes PlayCanvas Editor functionalities as structured data and APIs, allowing AI models to read context and perform actions.
Can I customize the editor-mcp-server for specific game development workflows?
Yes, the server is modular and can be extended or configured to fit custom automation and integration needs.
Does the editor-mcp-server support real-time collaboration features?
While primarily focused on AI automation, it can be integrated with collaboration tools to enhance team workflows.
What programming languages are used in the editor-mcp-server?
The server is typically implemented in JavaScript/TypeScript to align with PlayCanvas Editor's web-based environment.