Terminal Controller MCP Server

What does “Terminal Controller” MCP Server do?

The Terminal Controller MCP Server is a Model Context Protocol (MCP) server designed to enable secure execution of terminal commands, directory navigation, and file system operations via a standardized interface. It acts as a bridge between AI assistants and the host environment, allowing AI agents to perform tasks such as running shell commands, managing directories, and manipulating files programmatically. With built-in security safeguards, command history tracking, and cross-platform compatibility, Terminal Controller enhances development workflows by giving AI-powered tools controlled access to a machine’s terminal and filesystem. This capability empowers AI assistants to automate, explore, and manage system-level tasks for developers in a safe and standardized way.

List of Prompts

No prompt templates were found in the repository or documentation.

List of Resources

No explicit MCP resources were defined in the repository or documentation.

List of Tools

• Command Execution: Allows running terminal commands with timeout controls and captures comprehensive output.
• Directory Management: Enables navigation and listing of directory contents with intuitive formatting.
• File Operations: Supports reading, writing, updating, inserting, and deleting file content with row-level precision.
• Command History: Tracks and displays recent command executions for auditing and repeatability.

Use Cases of this MCP Server

• Automated Command Execution: Developers can instruct AI assistants to safely run shell commands for building, testing, or deploying code, with output and errors captured.
• Directory and File Management: AI agents can help organize, browse, or manipulate files and folders, making it easier to automate codebase exploration or environment setup.
• Security-Conscious Scripting: Built-in safeguards help prevent dangerous commands, reducing risk when granting AI terminal access.
• System Monitoring and Auditing: Command history features allow for tracking what actions were performed, aiding in audits and workflow transparency.
• Cross-Platform Development: By supporting both Windows and UNIX-based systems, the MCP server facilitates consistent development experiences across diverse environments.

How to set it up

Windsurf

1. Ensure Python 3.11+ is installed.
2. Install the package via PyPI:

   pip install terminal-controller
   

3. Edit your Windsurf configuration file to add the MCP server:

   {
     "mcpServers": {
       "terminal-controller": {
         "command": "python",
         "args": ["-m", "terminal_controller"]
       }
     }
   }
   

4. Save the configuration and restart Windsurf.
5. Verify the MCP server is running and accessible.

Claude

1. Install Python 3.11+ on your machine.
2. For Claude Desktop, install via Smithery:

   npx -y @smithery/cli install @GongRzhe/terminal-controller-mcp --client claude
   

3. Alternatively, install via PyPI:

   pip install terminal-controller
   

4. Add the following to your Claude configuration:

   {
     "mcpServers": {
       "terminal-controller": {
         "command": "python",
         "args": ["-m", "terminal_controller"]
       }
     }
   }
   

5. Restart Claude Desktop and ensure the MCP server is detected.

Cursor

1. Ensure Node.js and Python 3.11+ are installed.
2. Install terminal-controller:

   pip install terminal-controller
   

3. Add the MCP server to your Cursor config:

   {
     "mcpServers": {
       "terminal-controller": {
         "command": "python",
         "args": ["-m", "terminal_controller"]
       }
     }
   }
   

4. Save the file and restart Cursor.
5. Confirm integration by checking the tool list in Cursor.

Cline

1. Make sure Python 3.11+ is available.
2. Install the MCP server:

   pip install terminal-controller
   

3. Add the following snippet to your Cline configuration:

   {
     "mcpServers": {
       "terminal-controller": {
         "command": "python",
         "args": ["-m", "terminal_controller"]
       }
     }
   }
   

4. Restart Cline after saving changes.
5. Test by running a simple command through the MCP interface.

Securing API Keys

If API keys or secrets are required for your setup, use environment variables rather than hardcoding them. Example configuration:

{
  "mcpServers": {
    "terminal-controller": {
      "command": "python",
      "args": ["-m", "terminal_controller"],
      "env": {
        "MY_API_KEY": "${MY_API_KEY_ENV_VAR}"
      },
      "inputs": {
        "api_key": "${MY_API_KEY_ENV_VAR}"
      }
    }
  }
}

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:

{
  "terminal-controller": {
    "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 “terminal-controller” to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.

Overview

Based on the above, Terminal Controller MCP provides essential terminal and filesystem access in a secure fashion, but lacks prompt templates and explicit resources. Its configuration is well-documented and cross-platform. Roots and sampling are not mentioned. Overall, this is a practical, safe, but relatively simple server for core DevOps or automation needs.

MCP Score