Unreal Engine▌
by runreal
Integrate Unreal Engine with your workflow. Streamline game development using Unreal Engine 5 and UE Engine tools for ma
Integrates with Unreal Engine to assist with game development workflows.
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / Game developers using Unreal Engine 5.4+
- / Automating asset management tasks
- / AI-assisted game development workflows
capabilities
- / Execute Python scripts in Unreal Editor
- / List and query project assets
- / Export assets to text format
- / Get asset information and references
- / Run console commands in Unreal
- / Configure engine and project paths
what it does
Connects to Unreal Engine projects to execute Python scripts, query assets, and run console commands directly from AI assistants. Uses Unreal's built-in Python remote execution without requiring custom plugins.
about
Unreal Engine is a community-built MCP server published by runreal that provides AI assistants with tools and capabilities via the Model Context Protocol. Integrate Unreal Engine with your workflow. Streamline game development using Unreal Engine 5 and UE Engine tools for ma It is categorized under developer tools. This server exposes 20 tools that AI clients can invoke during conversations and coding sessions.
how to install
You can install Unreal Engine in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
license
MIT
Unreal Engine is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
unreal-mcp
MCP server for Unreal Engine that uses Unreal Python Remote Execution


⚡ Differences
This server does not require installing a new UE plugin as it uses the built-in Python remote execution protocol.
Adding new tools/features is much faster to develop since it does not require any C++ code.
It can support the full Unreal Engine Python API
⚠️ Note
- This is not an official Unreal Engine project.
- Your AI agents or tools will have full access to your Editor.
- Review any changes your Client suggests before you approve them.
📦 Installation
📋 Requirements
- 🔧 Unreal Engine 5.4+ (verified, may work with earlier versions)
- 🟢 Node.js with npx
- 🤖 MCP Client (Claude, Cursor, etc.)
- Setting up your Editor:
- Open your Unreal Engine project
- Go to
Edit->Plugins - Search for "Python Editor Script Plugin" and enable it
- Restart the editor if prompted
- Go to
Edit->Project Settings - Search for "Python" and enable the "Enable Remote Execution" option

- Set up your Client:
- Edit your Claude (or Cursor) config
{
"mcpServers": {
"unreal": {
"command": "npx",
"args": [
"-y",
"@runreal/unreal-mcp"
]
}
}
}
🔧 Troubleshooting
If you get an error similar to MCP Unreal: Unexpected token 'C', Connection... it means that the mcp-server was not able to connect to the Unreal Editor.
- Make sure that the Python Editor Script Plugin is enabled and that the Remote Execution option is checked in your project settings.
- Try also changing your bind address from
127.0.0.1to0.0.0.0but note that this will allow connections from your local network. - Restart your Unreal Editor fully.
- Fully close/open your client (Claude, Cursor, etc.) to ensure it reconnects to the MCP server. (
File -> Exiton windows). - Check your running processes and kill any zombie unreal-mcp Node.js processes.
🛠️ Available Tools
| Tool | Description |
|---|---|
set_unreal_engine_path | Set the Unreal Engine path |
set_unreal_project_path | Set the Project path |
get_unreal_engine_path | Get the current Unreal Engine path |
get_unreal_project_path | Get the current Unreal Project path |
editor_run_python | Execute any python within the Unreal Editor |
editor_list_assets | List all Unreal assets |
editor_export_asset | Export an Unreal asset to text |
editor_get_asset_info | Get information about an asset, including LOD levels for StaticMesh and SkeletalMesh assets |
editor_get_asset_references | Get references for an asset |
editor_console_command | Run a console command in Unreal |
editor_project_info | Get detailed information about the current project |
editor_get_map_info | Get detailed information about the current map/level |
editor_search_assets | Search for assets by name or path with optional class filter |
editor_get_world_outliner | Get all actors in the current world with their properties |
editor_validate_assets | Validate assets in the project to check for errors |
editor_create_object | Create a new object/actor in the world |
editor_update_object | Update an existing object/actor in the world |
editor_delete_object | Delete an object/actor from the world |
editor_take_screenshot | Take a screenshot of the Unreal Editor |
editor_move_camera | Move the viewport camera to a specific location and rotation for positioning screenshots |
🤝 Contributing
Please feel free to open issues or pull requests. Contributions are welcome, especially new tools/commands.
<a href="https://glama.ai/mcp/servers/@runreal/unreal-mcp"> <img width="380" height="200" src="https://glama.ai/mcp/servers/@runreal/unreal-mcp/badge" /> </a>License MIT
FAQ
- What is the Unreal Engine MCP server?
- Unreal Engine is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for Unreal Engine?
- This profile displays 73 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.6 out of 5—verify behavior in your own environment before production use.
Use Cases▌
Extended AI Capabilities
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Context Enhancement
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Workflow Automation
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Implementation Guide▌
Prerequisites
- ›Claude Desktop 0.7.0+ or Cursor IDE with MCP support
- ›Basic understanding of MCP architecture and capabilities
- ›Access credentials for integrated services (if required)
- ›Willingness to experiment and iterate on configuration
Time Estimate
15-60 minutes depending on server complexity
Installation Steps
- 1.Install MCP server: npm install -g [package-name] or via GitHub
- 2.Add server configuration to ~/.claude/mcp.json
- 3.Provide required credentials and configuration
- 4.Restart Claude Desktop to load new server
- 5.Test basic functionality with simple prompts
- 6.Explore capabilities and experiment with use cases
- 7.Document successful patterns for reuse
Troubleshooting
- ⚠MCP server not loading: Check config syntax, verify installation
- ⚠Connection errors: Check network, firewall, credentials
- ⚠Feature not working: Read server docs, check required parameters
- ⚠Performance issues: Monitor resource usage, check for network latency
- ⚠Conflicts with other servers: Check port assignments, namespace collisions
Best Practices▌
✓ Do
- +Read server documentation thoroughly before setup
- +Start with simple use cases to validate functionality
- +Test in non-production environment first
- +Monitor resource usage and performance
- +Keep servers updated for bug fixes and new features
- +Document configuration for team members
- +Use environment variables for sensitive configuration
✗ Don't
- −Don't grant overly permissive access to MCP servers
- −Don't skip reading security considerations in docs
- −Don't expose sensitive data without proper controls
- −Don't run untrusted MCP servers without code review
- −Don't ignore error messages—investigate root cause
💡 Pro Tips
- ★Combine multiple MCP servers for powerful workflows
- ★Create custom MCP servers for your specific needs
- ★Share successful configurations with team
- ★Use MCP inspector for debugging
- ★Join MCP community for tips and troubleshooting
Technical Details▌
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
- Model Context Protocol (MCP)
- JSON-RPC 2.0
- stdio or HTTP transport
Compatibility
- Claude Desktop
- Cursor IDE
- Custom MCP clients
When to Use This▌
✓ Use When
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid When
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.
Integration▌
- →Tool composition: Chain multiple MCP tools in workflows
- →Context augmentation: Provide AI with relevant external data
- →Action delegation: Let AI execute tasks on external systems
- →Bidirectional sync: Keep AI context and external systems in sync
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
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Ratings
4.6★★★★★73 reviews- ★★★★★Zaid Ramirez· Dec 24, 2024
Unreal Engine is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Noor Ndlovu· Dec 12, 2024
Unreal Engine is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Dhruvi Jain· Dec 8, 2024
Unreal Engine is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Noor Gill· Dec 8, 2024
Unreal Engine reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Noor Gonzalez· Dec 8, 2024
Strong directory entry: Unreal Engine surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Oshnikdeep· Nov 27, 2024
Unreal Engine is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Hassan Lopez· Nov 27, 2024
Useful MCP listing: Unreal Engine is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Charlotte Huang· Nov 27, 2024
We wired Unreal Engine into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
- ★★★★★Olivia Iyer· Nov 15, 2024
Unreal Engine is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Charlotte Patel· Nov 3, 2024
Unreal Engine is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
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