Coolify AnythingLLM MCP
Coolify & AnythingLLM MCP Server 🚀
An official Model Context Protocol (MCP) server that connects your AnythingLLM chat interface directly to your self-hosted Coolify infrastructure. Manage, deploy, and troubleshoot your production servers using natural language.
Developed and maintained by the team behind xlop.cz – the Czech tech hub for AI & Self-Hosting innovations.
🧠 Why this project?
Giving AI agents the power to write code is great, but giving them the context of your infrastructure is a game-changer. This MCP server acts as a secure bridge:
AnythingLLM acts as the intelligent agent and UI.
MCP (Model Context Protocol) provides the secure communication standard.
Coolify API executes the infrastructure tasks on your home lab or VPS.
🌟 Key Features
App Diagnostics: Ask your AI about active applications, container status, and resources.
Log Fetching: Let the AI read application and deployment logs to troubleshoot bugs in seconds.
Deployment Automation: Trigger new builds, restarts, or rollbacks using simple prompts.
Secure by Design: No hardcoded credentials. Everything runs via Environment Variables.
🛠️ Installation & Setup
1. Prerequisites
A running Coolify instance with an API Token (generated in your Coolify settings).
AnythingLLM (Desktop app or self-hosted via Docker).
Node.js (v18+) or Docker environment to run this MCP server.
2. Environment Setup
Create a .env file in the root directory of this project:
COOLIFY_API_URL=[https://your-coolify-instance.com/api/v1](https://your-coolify-instance.com/api/v1)
COOLIFY_API_TOKEN=your_secret_coolify_api_token
3. Connect to AnythingLLM
Open your AnythingLLM settings, navigate to Agent Custom Tools / MCP Servers, and add this server using the following configuration:
Mode:
stdioCommand:
nodeArgs:
["/path/to/coolify-anythingllm-mcp/dist/index.js"]
(Alternatively, run it via Docker using the provided Dockerfile).
🤖 Awesome Prompts to Try
Once connected, open a chat in AnythingLLM and try these:
"List all running applications on my Coolify server."
"Check the deployment logs for my frontend app. Why did it fail?"
"Restart the PostgreSQL database container immediately."
⚠️ Disclaimer & Safety
Running AI with infrastructure access is powerful but experimental.
We strongly recommend running your AI agent with Human-in-the-loop confirmations enabled.
The authors are not responsible for any server downtime, data loss, or accidental resource deletion caused by your AI model.
📄 License
This project is open-source and licensed under the MIT License - see the LICENSE file for details.
Built with ❤️ for the open-source community by xlop.cz.