Interactive Shell MCP

Interactive Shell MCP

Enables LLMs to create and manage persistent, interactive shell sessions with full terminal emulation and PTY support. It allows for sequential command execution and supports interactive programs like vim or htop through specialized streaming and snapshot output modes.

Category
Visit Server

README

Interactive Shell MCP

MCP server that provides interactive shell session management with full terminal emulation support via node-pty

Overview

The Interactive Shell MCP (Model Context Protocol) server enables LLMs to create and manage interactive shell sessions. It provides persistent shell environments where commands can be executed sequentially while maintaining state, similar to how a human would use a terminal.

Features

  • Create and manage multiple concurrent shell sessions
  • Full terminal emulation with proper TTY support
  • Persistent shell state across commands
  • Support for interactive programs (vim, nano, etc.)
  • Cross-platform support (bash on Unix/Linux/macOS, PowerShell on Windows)
  • Smart output handling with automatic mode detection
  • Snapshot mode for continuously updating terminal applications
  • Configurable output size limits to prevent memory overflow
  • Automatic detection of terminal control sequences

Available Tools

start_shell_session

Spawns a new PTY shell and returns a unique session ID.

  • Input: None
  • Output: { sessionId: string }

send_shell_input

Writes input to the PTY with automatic newline handling.

  • Input:
    • sessionId (string): The session ID of the shell
    • input (string): The input to send to the shell
  • Output: Success confirmation

read_shell_output

Returns output from the PTY process with support for two modes:

  • Streaming mode (default): Returns buffered output since last read and clears the buffer

  • Snapshot mode: Returns the current terminal screen state without clearing (ideal for apps like top, htop, airodump-ng)

  • Input:

    • sessionId (string): The session ID of the shell
    • mode (string, optional): Output mode - "streaming" (default) or "snapshot"
    • maxBytes (number, optional): Maximum bytes to return (default: 100KB, max: 1MB)
    • snapshotSize (number, optional): Size of the snapshot buffer to capture (default: 50KB)
  • Output:

    {
      "output": "string",
      "metadata": {
        "mode": "streaming|snapshot",
        "totalBytesReceived": number,
        "truncated": boolean,
        "originalSize": number,
        "isSnapshot": boolean,
        "snapshotTime": number
      }
    }
    

end_shell_session

Closes the PTY and cleans up resources.

  • Input:
    • sessionId (string): The session ID of the shell to close
  • Output: Success confirmation

Installation

npm install
npm run build

MCP Configuration

To use this MCP server with Claude Desktop or VS Code, add the following configuration to your MCP settings file:

Claude Desktop

Add to ~/Library/Application Support/Claude/claude_desktop_config.json on macOS or %APPDATA%\Claude\claude_desktop_config.json on Windows:

{
  "mcpServers": {
    "Interactive Shell MCP": {
      "command": "node",
      "args": [
        "/path/to/interactive-shell-mcp/dist/server.js"
      ]
    }
  }
}

VS Code (Cursor)

Add to ~/.cursor/mcp.json:

{
  "mcpServers": {
    "Interactive Shell MCP": {
      "command": "node",
      "args": [
        "/path/to/interactive-shell-mcp/dist/server.js"
      ]
    }
  }
}

Replace /path/to/interactive-shell-mcp with the actual path to your installation.

Usage Examples

Note: The examples below demonstrate how an LLM would interact with this MCP server. These are not JavaScript code to be run directly, but rather illustrate the expected tool calling patterns.

Working with High-Output Commands

When working with commands that produce large outputs or continuously refresh the screen (like airodump-ng, htop, top), use snapshot mode:

// Example of how an LLM would call these tools:
// Start a session
const { sessionId } = await start_shell_session();

// Run airodump-ng
await send_shell_input(sessionId, "sudo airodump-ng wlan0mon");

// Read output in snapshot mode to get current screen state
const result = await read_shell_output(sessionId, {
  mode: "snapshot"
});

Handling Regular Commands

For normal commands that produce streaming output:

// Example of how an LLM would call these tools:
// Use default streaming mode
const output = await read_shell_output(sessionId);

// Or explicitly set a size limit for very large outputs
const output = await read_shell_output(sessionId, {
  maxBytes: 50000  // Return only last 50KB
});

Output Modes Explained

  • Streaming Mode: Best for regular commands. Returns all output since last read and clears the buffer.
  • Snapshot Mode: Best for continuously updating applications. Returns the current terminal screen state without clearing. The server automatically switches to this mode when it detects terminal control sequences.

Debugging

To run the server independently for debugging:

npm start

This will start the server on stdio, which is primarily useful for testing the installation and debugging issues.

License

MIT

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured