UnityAutonomousMCP
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@followed by the MCP server name and your instructions, e.g., "@UnityAutonomousMCPinspect scene and update scripts"
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Here is a step-by-step guide with screenshots.
Unity Autonomous Agent MCP
🤖 A comprehensive autonomous agent framework for Unity 2022.3.22f1 that combines the power of Model Context Protocol (MCP) with advanced AI decision-making capabilities.
🌟 Key Features
🧠 Autonomous Agent Capabilities
Intelligent Task Planning: AI-driven task decomposition and execution planning
Decision Making: Context-aware decision trees with learning capabilities
Self-Improvement: Continuous learning from user interactions and outcomes
Multi-Agent Coordination: Support for multiple autonomous agents working together
🎮 Unity Integration
Full Editor Control: Complete Unity Editor automation and manipulation
Runtime AI: In-game autonomous NPC behavior and debugging
Asset Management: Intelligent asset creation, optimization, and organization
Scene Management: Automated scene setup, optimization, and testing
🔧 Advanced MCP Features
Extensible Architecture: Plugin-based system for custom tools and handlers
Real-time Communication: Low-latency TCP/IP communication with external AI services
Multi-Provider Support: Compatible with Claude, GPT, Gemini, and custom LLM providers
Resource Management: Intelligent resource allocation and optimization
Related MCP server: Union Unity MCP Server
🏗️ Architecture Overview
┌─────────────────────────────────────────────────────────────┐
│ Unity Autonomous Agent MCP │
├─────────────────────────────────────────────────────────────┤
│ ┌─────────────────┐ ┌─────────────────┐ ┌──────────────┐ │
│ │ Agent Core │ │ Task Planner │ │ Decision │ │
│ │ │ │ │ │ Engine │ │
│ │ - State Mgmt │ │ - Task Decomp │ │ - ML Models │ │
│ │ - Learning │ │ - Priority │ │ - Context │ │
│ │ - Memory │ │ - Scheduling │ │ - Reasoning │ │
│ └─────────────────┘ └─────────────────┘ └──────────────┘ │
├─────────────────────────────────────────────────────────────┤
│ ┌─────────────────┐ ┌─────────────────┐ ┌──────────────┐ │
│ │ MCP Server │ │ Unity Bridge │ │ Plugin │ │
│ │ │ │ │ │ System │ │
│ │ - Protocol │ │ - Editor API │ │ - Custom │ │
│ │ - Handlers │ │ - Runtime API │ │ Tools │ │
│ │ - Transport │ │ - Asset Mgmt │ │ - Extensions │ │
│ └─────────────────┘ └─────────────────┘ └──────────────┘ │
├─────────────────────────────────────────────────────────────┤
│ Unity Engine (2022.3.22f1) │
└─────────────────────────────────────────────────────────────┘📋 Requirements
Unity 2022.3.22f1 or later (tested up to Unity 6.1)
.NET/C# 9.0
Node.js 18.0.0+ with npm (for TypeScript server)
Python 3.8+ (for ML/AI components)
External LLM Provider (Claude, OpenAI, Gemini, or custom)
🚀 Quick Start
Re-analysis details and capability gaps are documented in
docs/capability-matrix.md.
1. Installation
# Clone the repository
git clone https://github.com/KinofSin/UnityAutonomousMCP.git
cd UnityAutonomousMCP
# Install Unity Package
# In Unity Editor: Window > Package Manager > Add package from git URL
# Enter: file:///path/to/UnityAutonomousMCP/com.autonomous-unity.mcp2. Setup TypeScript Server
npm install
npm run build
npm run smokenpm run smoke validates planner + executor behavior (including run_tests -> get_test_job polling) for both successful and failed test-job terminal paths, without requiring a live Unity Editor.
3. Run modes
# Autonomous bootstrap (local dry-run using mock Unity bridge)
npm run dev -- -- "inspect scene and update scripts"
# MCP stdio mode (for Claude/Cursor/Windsurf MCP client config)
npm run dev -- --mcp
# Force mock bridge explicitly
npm run dev -- --mock -- "inspect scene and update scripts"4. Transport bridge configuration (real Unity connection)
Unity package host (inside Unity Editor) serves both transports:
HTTP endpoint:
POST /mcp/toolonUNITY_HTTP_PORT(default8080)TCP endpoint: newline-delimited JSON on
UNITY_TCP_PORT(default8081)
Node-side bridge environment variables:
UNITY_TRANSPORT=http # http | tcp | mock
UNITY_HOST=127.0.0.1
UNITY_HTTP_PORT=8080
UNITY_TCP_PORT=8081
UNITY_TIMEOUT_MS=10000
UNITY_TEST_POLL_ATTEMPTS=30
UNITY_TEST_POLL_INTERVAL_MS=1000
UNITY_TEST_POLL_TIMEOUT_MS=1200005. Configure Claude Desktop
{
"mcpServers": {
"unity-autonomous-agent": {
"command": "node",
"args": ["path/to/server/dist/index.js"],
"env": {
"UNITY_HOST": "localhost",
"UNITY_TRANSPORT": "http",
"UNITY_HTTP_PORT": "8080",
"UNITY_TCP_PORT": "8081",
"AI_PROVIDER": "anthropic",
"AI_API_KEY": "your-api-key"
}
}
}
}6. Start Using
Open Unity Project
Navigate to
Edit > Preferences > Autonomous Agent MCPConfigure host + HTTP/TCP ports
Click "Connect" to start Unity transport host
Start MCP server (
npm run dev -- --mcp)Begin interacting with AI through your preferred MCP client
✅ Current implementation status (this repo)
Capability matrix + gap analysis:
docs/capability-matrix.mdAutonomous planner core:
server/src/planner.tsPolicy guardrails:
server/src/policy.tsPlan executor:
server/src/executor.tsMCP server tools (
autonomous_plan,unity_tool_call,list_capabilities):server/src/mcpServer.tsReal Unity bridge transports (HTTP/TCP + env-driven mode):
server/src/unityBridge.tsConcrete step contracts for autonomous_plan:
server/src/contracts.tsUnity 2022.3.22f1 package scaffold:
com.autonomous-unity.mcp/Editor settings/provider:
Editor/AutonomousMcpSettingsProvider.csReal transport host:
Editor/AutonomousMcpTransportHost.csTool dispatcher:
Editor/AutonomousMcpToolDispatcher.csRuntime entry component:
Runtime/AutonomousMcpRuntime.cs
🔁 End-to-end autonomous_plan contract mapping
autonomous_plan now emits concrete Unity tool payloads:
read_console→{ level, limit }manage_scene→{ action: "inspect_active_scene" }manage_script→{ action: "create_or_update", scriptPath, contents }(when goal implies code changes)validate_script→{ strict }(after script edits)run_tests→{ mode }(when goal mentions tests; returnsjobId)get_test_job→{ jobId }(executor polls untilcompletedorfailed)batch_execute→{ operations: [{ tool: "manage_scene", params: { action: "save_active_scene" } }] }
Test execution flow
run_testsstarts an async Unity Test Runner job (editmodeorplaymode)Server receives
{ jobId, status: "queued" }Executor automatically calls
get_test_jobuntil terminal stateFinal test summary (passed/failed/skipped + per-test details) is included in execution results
Test polling policy limits
UNITY_TEST_POLL_ATTEMPTS: max polling iterations forget_test_job(clamped 1..300)UNITY_TEST_POLL_INTERVAL_MS: delay between polls in milliseconds (clamped 100..60000)UNITY_TEST_POLL_TIMEOUT_MS: overall timeout for polling cycle (clamped 1000..1800000)
🤖 Autonomous Agent Features
Intelligent Task Planning
Goal Decomposition: Break complex tasks into manageable subtasks
Priority Management: Dynamic task prioritization based on context
Resource Allocation: Optimal distribution of system resources
Dependency Resolution: Handle task dependencies and conflicts
Learning & Adaptation
Pattern Recognition: Learn from user behavior and preferences
Performance Optimization: Improve efficiency over time
Error Recovery: Learn from mistakes and avoid repetition
Context Awareness: Adapt to project-specific requirements
Multi-Agent Coordination
Agent Communication: Coordinate multiple specialized agents
Task Distribution: Distribute workload across agent instances
Conflict Resolution: Handle competing priorities and resource conflicts
Collaborative Problem Solving: Combine multiple agent perspectives
🔧 MCP Tools & Capabilities
🎮 Unity Editor Tools
Scene Management: Create, modify, optimize scenes automatically
Asset Operations: Intelligent asset creation and organization
GameObject Control: Advanced object manipulation and optimization
Component Management: Dynamic component addition and configuration
Build Automation: Automated build processes and optimization
🧩 Advanced Development Tools
Code Generation: AI-assisted script writing and optimization
Testing Automation: Automated test creation and execution
Performance Analysis: Real-time performance monitoring and optimization
Debugging Assistant: Intelligent error detection and resolution
Documentation Generation: Auto-generate technical documentation
🎯 Runtime AI Features
NPC Behavior: Dynamic, intelligent NPC behavior systems
Game Balance: Automated game balance testing and adjustment
Player Analytics: Real-time player behavior analysis
Dynamic Difficulty: Adaptive difficulty adjustment systems
Content Generation: Procedural content creation and optimization
🔌 Plugin System
Create custom plugins to extend functionality:
[AutonomousPlugin("custom-tool")]
public class CustomToolPlugin : IAutonomousTool
{
public async Task<ToolResult> ExecuteAsync(ToolContext context)
{
// Your custom tool logic
return new ToolResult { Success = true, Data = result };
}
}📊 Performance & Monitoring
Real-time Metrics
Agent Performance: Monitor agent efficiency and accuracy
Resource Usage: Track CPU, memory, and network utilization
Task Completion: Measure task success rates and timing
Learning Progress: Track agent improvement over time
Optimization Features
Caching System: Intelligent caching for frequently used data
Batch Processing: Optimize multiple operations together
Predictive Loading: Anticipate and preload required resources
Adaptive Performance: Adjust performance based on system capabilities
🛡️ Security & Safety
Safety Measures
Sandboxed Execution: Isolate agent operations from critical systems
Permission System: Granular control over agent capabilities
Audit Logging: Complete audit trail of all agent actions
Rollback Capability: Undo system for agent modifications
Best Practices
Regular Backups: Automatic backup before major operations
Validation Checks: Verify operation safety before execution
User Confirmation: Require confirmation for destructive operations
Error Handling: Comprehensive error recovery mechanisms
🤝 Contributing
We welcome contributions! Please see our Contributing Guide for details.
Development Setup
Clone repository
Install dependencies (
npm installin server directory)Open Unity project
Enable Developer Mode in preferences
Start contributing!
📄 License
This project is licensed under the MIT License - see the LICENSE file for details.
🙏 Acknowledgments
Built upon the excellent foundations of Unity-MCP and UnityMCP
Inspired by the latest advances in autonomous agents and AI decision-making
Community feedback and contributions have been invaluable
🚀 Ready to transform your Unity development with AI-powered autonomy?
Start building intelligent, self-improving Unity projects today!
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