jchambless

MonoGame MCP Server

Community jchambless
Updated

MonoGame MCP Server

npm versionLicense: MIT

A Model Context Protocol (MCP) server for the MonoGame framework. It provides AI-powered documentation lookup, project management, code scaffolding, and diagnostic tools for MonoGame development.

Quick Start

  1. Install prerequisites (.NET SDK 8.0 and MonoGame templates).
  2. Configure your MCP client (like Claude Desktop) to use npx monogame-mcp.
  3. Restart your client and start building MonoGame projects.

Prerequisites

  • Node.js: version 18 or higher.
  • .NET SDK 8.0: Required for building and running projects. Verify with dotnet --version.
  • MonoGame Templates: Install with dotnet new install MonoGame.Templates.CSharp.
  • MGCB Tool: Install for content builds with dotnet tool install -g dotnet-mgcb.

Installation

Using npx (Recommended)

You can run the server directly without local installation:

npx monogame-mcp

Global Installation

npm install -g monogame-mcp

Docker

docker run -i monogame-mcp

Configuration

Claude Desktop

Add this to your claude_desktop_config.json:

{
  "mcpServers": {
    "monogame-mcp": {
      "command": "npx",
      "args": ["-y", "monogame-mcp"]
    }
  }
}

If using Docker:

{
  "mcpServers": {
    "monogame-mcp": {
      "command": "docker",
      "args": ["run", "-i", "monogame-mcp"]
    }
  }
}

Available Tools

Tool Name Description Example Usage
monogame_api_lookup Search MonoGame API documentation for classes, methods, and properties { "query": "SpriteBatch" }
monogame_create_project Create a new MonoGame project using dotnet templates { "projectName": "MyGame", "template": "desktopgl" }
monogame_manage_content Add, remove, or configure assets in a .mgcb content project { "action": "add", "mgcbPath": "Content.mgcb", "assetPath": "player.png" }
monogame_build_content Build MonoGame content using MGCB CLI { "mgcbPath": "Content/Content.mgcb" }
monogame_scaffold_code Generate MonoGame C# code from predefined templates { "template": "game-class", "className": "MainGame" }
monogame_diagnose_error Diagnose MonoGame error messages and suggest fixes { "errorMessage": "Could not find ContentTypeReader" }
monogame_build_run Build or run MonoGame projects using dotnet CLI { "action": "run", "projectPath": "MyGame.csproj" }

Available Resources

URI Template Description Example URI
monogame://api/{className} API reference documentation for MonoGame classes monogame://api/Texture2D
monogame://examples/{topic} Code examples and tutorials for development monogame://examples/sprite-animation
monogame://content-pipeline/{topic} Documentation for the Content Pipeline monogame://content-pipeline/overview
monogame://platforms/{platform} Platform-specific guides monogame://platforms/android

Available Prompts

Prompt Name Arguments Description
monogame_code_review code (required), focus Review C# code for MonoGame best practices
monogame_troubleshoot error (required), code, platform Troubleshoot errors and exceptions
monogame_architecture gameType (required), features, scale Plan game architecture and organization
monogame_implement_feature feature (required), existingCode, platform Step-by-step feature implementation guidance

Examples

1. Creating a New Project

Tell the AI: "Create a new MonoGame DesktopGL project named SpaceExplorer, add a background.png texture to content, and build it."The AI will use monogame_create_project, then monogame_manage_content, and finally monogame_build_content.

2. Learning the API

Ask: "How do I use SpriteBatch to draw a scaled texture?"The AI will use monogame_api_lookup or read monogame://api/SpriteBatch to provide exact parameters and code.

3. Fixing Errors

If you get an error: "ContentLoadException: The content file was not found."Provide the error to the AI. It will use monogame_diagnose_error to identify that you likely missed adding the asset to your .mgcb file or have a path mismatch.

4. Scaffolding and Running

Ask: "Generate a scene manager class for my game and then try to run the project."The AI will use monogame_scaffold_code with the scene-manager template, then monogame_build_run with the run action.

Development

  1. Clone the repository.
  2. Install dependencies: npm install
  3. Build the project: npm run build
  4. Run tests: npm test
  5. Link for local testing: npm link

License

MIT

MCP Server · Populars

MCP Server · New

    easyshell-ai

    EasyShell

    Lightweight server management & intelligent ops platform with Docker one-click deployment, batch script execution, web terminal, and AI-powered operations.

    Community easyshell-ai
    AVIDS2

    Memorix

    Cross-Agent Memory Bridge Persistent memory for AI coding agents across 10 IDEs (Cursor, Windsurf, Claude Code, Codex, Copilot, Kiro, Antigravity, OpenCode, Trae, Gemini CLI) via MCP. Team collaboration, auto-cleanup, mini-skills, workspace sync. Never re-explain your project again.

    Community AVIDS2
    zw008

    VMware AIops

    VMware vCenter/ESXi AI-powered monitoring and operations. Two skills: vmware-monitor (read-only, safe) and vmware-aiops (full operations) | Claude Code Skill

    Community zw008
    Dave-London

    Pare

    Dev tools, optimized for agents. Structured, token-efficient MCP servers for git, test runners, npm, Docker, and more.

    Community Dave-London
    luckyPipewrench

    Pipelock

    Firewall for AI agents. DLP scanning, SSRF protection, bidirectional MCP scanning, tool poisoning detection, and workspace integrity monitoring.

    Community luckyPipewrench