1Panel MCP Server Integration

What does “1Panel” MCP Server do?

The 1Panel MCP Server is an implementation of the Model Context Protocol (MCP) server designed specifically for integration with 1Panel. It serves as a bridge connecting AI assistants with the 1Panel platform, enabling enhanced development workflows by allowing AI agents to interact programmatically with 1Panel’s APIs and data sources. By deploying this server, developers can use AI-powered tools to automate and streamline common administrative and operational tasks within their 1Panel environments, such as querying system status, managing files, or executing control commands. The server supports multiple transport methods (stdio and sse), offering flexibility for integration in various environments, and can be securely configured with API tokens and host addresses.

List of Prompts

No prompt templates are mentioned in the available documentation or code.

List of Resources

No explicit MCP resources are described in the available documentation or code.

List of Tools

No specific tools are listed or described in the available documentation or code (e.g., server.py does not exist in this Go-based project).

Use Cases of this MCP Server

• 1Panel Automation: Integrate AI assistants to automate 1Panel administrative tasks, such as service restarts, user management, or status checks via standardized AI commands.
• Remote Operations: Allow AI-driven scripts or workflows to interact with 1Panel servers remotely, enhancing DevOps and system administration capabilities.
• SSE/Streaming AI Integration: Enable real-time interactions between 1Panel and AI agents using SSE transport mode, allowing live monitoring and prompt responses.
• Secure Programmatic Access: Use access tokens and environment-based configuration to securely expose only the necessary parts of 1Panel to AI agents, maintaining operational safety.

How to set it up

Windsurf

1. Ensure you have the 1Panel MCP Server binary or Docker image.

2. Obtain your 1Panel access token and host URL.

3. Edit the Windsurf configuration file.

4. Add the following JSON snippet under mcpServers:

   {
     "mcpServers": {
       "mcp-1panel": {
         "command": "mcp-1panel",
         "env": {
           "PANEL_ACCESS_TOKEN": "<your 1Panel access token>",
           "PANEL_HOST": "such as http://localhost:8080"
         }
       }
     }
   }
   

5. Save and restart Windsurf, then verify the server connection.

Docker Example

{
  "mcpServers": {
    "mcp-1panel": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "PANEL_HOST",
        "-e",
        "PANEL_ACCESS_TOKEN",
        "1panel/1panel-mcp-server"
      ],
      "env": {
        "PANEL_HOST": "such as http://localhost:8080",
        "PANEL_ACCESS_TOKEN": "<your 1Panel access token>"
      }
    }
  }
}

Claude

1. Download or build the 1Panel MCP Server.
2. Acquire your 1Panel API token and host info.
3. Open Claude’s configuration file.
4. Insert the same configuration as for Windsurf under mcpServers.
5. Save and restart Claude.

Cursor

1. Ensure 1Panel MCP Server is installed.

2. Get your access token and host URL.

3. Edit the Cursor configuration file.

4. Add:

   {
     "mcpServers": {
       "mcp-1panel": {
         "command": "mcp-1panel",
         "env": {
           "PANEL_ACCESS_TOKEN": "<your 1Panel access token>",
           "PANEL_HOST": "such as http://localhost:8080"
         }
       }
     }
   }
   

5. Save changes and restart Cursor.

SSE Mode Example

If using SSE mode, start the server with:

mcp-1panel -host http://localhost:8080 -token <your 1Panel access token> -transport sse -addr http://localhost:8000

Add to mcpServers:

{
  "mcpServers": {
    "mcp-1panel": {
      "url": "http://localhost:8000/sse"
    }
  }
}

Cline

1. Install the 1Panel MCP Server.
2. Set your PANEL_ACCESS_TOKEN and PANEL_HOST.
3. Edit the Cline configuration file and insert the same JSON as above.
4. Save and restart Cline.

Securing API Keys

Store API keys and sensitive info in environment variables. Example configuration:

{
  "mcpServers": {
    "mcp-1panel": {
      "command": "mcp-1panel",
      "env": {
        "PANEL_ACCESS_TOKEN": "${PANEL_ACCESS_TOKEN}",
        "PANEL_HOST": "${PANEL_HOST}"
      }
    }
  }
}

Replace ${PANEL_ACCESS_TOKEN} and ${PANEL_HOST} with your environment variable names.

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "MCP-name": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “MCP-name” to “mcp-1panel” and replace the URL with your own MCP server URL.

Overview

Our opinion

The 1Panel MCP Server offers clear installation and integration instructions and is actively maintained with a good number of stars and forks. However, the lack of detailed tool, prompt, and resource descriptions in the documentation limits its out-of-the-box usability for complex AI workflows. Based on the above, we rate this MCP implementation a 5/10 for completeness and developer friendliness.

MCP Score