
MCP Console Automation Server
Enables AI assistants to fully interact with console applications, monitor output, detect errors, and automate terminal workflows across multiple sessions. Similar to how Playwright works for web browsers but for command-line interfaces.
README
MCP Console Automation Server
Production-Ready Model Context Protocol (MCP) server that enables AI assistants to fully interact with console applications, monitor output, detect errors, and automate terminal workflows - similar to how Playwright works for web browsers.
Production Status ✅
This server is fully production-ready with:
- ✅ No native compilation required (removed node-pty dependency)
- ✅ Full cross-platform support (Windows, macOS, Linux)
- ✅ Streaming support for long-running processes
- ✅ Multiple console type support (cmd, PowerShell, bash, zsh, sh)
- ✅ Resource management and automatic cleanup
- ✅ Comprehensive error handling and recovery
- ✅ Easy installation scripts for all major MCP clients
- ✅ All tests passing (see test-functionality.js)
Features
- Full Terminal Control: Create and manage multiple console sessions simultaneously
- Interactive Input: Send text input and special key sequences (Enter, Tab, Ctrl+C, etc.)
- Real-time Output Monitoring: Capture and analyze console output as it happens
- Streaming Support: Efficient streaming for long-running processes
- Multiple Console Types: Support for cmd, PowerShell, bash, zsh, sh
- Automatic Error Detection: Built-in patterns to detect errors, exceptions, and stack traces
- Session Management: Create, stop, and manage up to 50 concurrent sessions
- Resource Management: Memory monitoring, automatic cleanup, session limits
- Command Execution: Run commands and wait for completion with timeout support
- Pattern Matching: Wait for specific output patterns before continuing
- Cross-platform: Works on Windows, macOS, and Linux without native dependencies
Quick Installation
Windows (PowerShell as Administrator)
git clone https://github.com/ooples/mcp-console-automation.git
cd mcp-console-automation
.\install.ps1 -Target claude # or google, openai, custom, all
macOS/Linux
git clone https://github.com/ooples/mcp-console-automation.git
cd mcp-console-automation
chmod +x install.sh
./install.sh --target claude # or google, openai, custom, all
Manual Installation
git clone https://github.com/ooples/mcp-console-automation.git
cd mcp-console-automation
npm install --production
npm run build
Configuration
For Claude Desktop
Add to your Claude Desktop configuration file:
Windows: %APPDATA%\Claude\claude_desktop_config.json
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Linux: ~/.config/Claude/claude_desktop_config.json
{
"mcpServers": {
"console-automation": {
"command": "npx",
"args": ["@mcp/console-automation"],
"env": {
"LOG_LEVEL": "info"
}
}
}
}
For other MCP clients
# Start the server
mcp-console --log-level info
# Or with npx
npx @mcp/console-automation --log-level info
Available Tools (12 Total)
console_create_session
Create a new console session for running commands.
Parameters:
command
(required): The command to executeargs
: Array of command argumentscwd
: Working directoryenv
: Environment variables objectdetectErrors
: Enable automatic error detection (default: true)timeout
: Session timeout in milliseconds
Example:
{
"command": "python",
"args": ["script.py"],
"cwd": "/path/to/project",
"detectErrors": true
}
console_send_input
Send text input to an active console session.
Parameters:
sessionId
(required): Session IDinput
(required): Text to send
console_send_key
Send special key sequences to a console session.
Parameters:
sessionId
(required): Session IDkey
(required): Key to send (enter, tab, up, down, ctrl+c, escape, etc.)
console_get_output
Retrieve output from a console session.
Parameters:
sessionId
(required): Session IDlimit
: Maximum number of output lines to return
console_wait_for_output
Wait for specific output pattern in console.
Parameters:
sessionId
(required): Session IDpattern
(required): Regex pattern to wait fortimeout
: Timeout in milliseconds (default: 5000)
console_execute_command
Execute a command and wait for completion.
Parameters:
command
(required): Command to executeargs
: Command argumentscwd
: Working directoryenv
: Environment variablestimeout
: Execution timeout
console_detect_errors
Analyze console output for errors and exceptions.
Parameters:
sessionId
: Session ID to analyzetext
: Direct text to analyze (if not using session)
console_stop_session
Stop an active console session.
Parameters:
sessionId
(required): Session ID to stop
console_list_sessions
List all active console sessions.
console_resize_session
Resize terminal dimensions for a session.
Parameters:
sessionId
(required): Session IDcols
(required): Number of columnsrows
(required): Number of rows
console_clear_output
Clear the output buffer for a session.
Parameters:
sessionId
(required): Session ID
Use Cases
1. Running and monitoring a development server
// Create a session for the dev server
const session = await console_create_session({
command: "npm",
args: ["run", "dev"],
detectErrors: true
});
// Wait for server to start
await console_wait_for_output({
sessionId: session.sessionId,
pattern: "Server running on",
timeout: 10000
});
// Monitor for errors
const errors = await console_detect_errors({
sessionId: session.sessionId
});
2. Interactive debugging session
// Start a Python debugging session
const session = await console_create_session({
command: "python",
args: ["-m", "pdb", "script.py"]
});
// Set a breakpoint
await console_send_input({
sessionId: session.sessionId,
input: "b main\n"
});
// Continue execution
await console_send_input({
sessionId: session.sessionId,
input: "c\n"
});
// Step through code
await console_send_key({
sessionId: session.sessionId,
key: "n"
});
3. Automated testing with error detection
// Run tests
const result = await console_execute_command({
command: "pytest",
args: ["tests/"],
timeout: 30000
});
// Check for test failures
const errors = await console_detect_errors({
text: result.output
});
if (errors.hasErrors) {
console.log("Test failures detected:", errors);
}
4. Interactive CLI tool automation
// Start an interactive CLI tool
const session = await console_create_session({
command: "mysql",
args: ["-u", "root", "-p"]
});
// Enter password
await console_wait_for_output({
sessionId: session.sessionId,
pattern: "Enter password:"
});
await console_send_input({
sessionId: session.sessionId,
input: "mypassword\n"
});
// Run SQL commands
await console_send_input({
sessionId: session.sessionId,
input: "SHOW DATABASES;\n"
});
Error Detection Patterns
The server includes built-in patterns for detecting common error types:
- Generic errors (error:, ERROR:, Error:)
- Exceptions (Exception:, exception)
- Warnings (Warning:, WARNING:)
- Fatal errors
- Failed operations
- Permission/access denied
- Timeouts
- Stack traces (Python, Java, Node.js)
- Compilation errors
- Syntax errors
- Memory errors
- Connection errors
Development
Building from source
npm install
npm run build
Running in development mode
npm run dev
Running tests
npm test
Type checking
npm run typecheck
Linting
npm run lint
Architecture
The server is built with:
- node-pty: For creating and managing pseudo-terminals
- @modelcontextprotocol/sdk: MCP protocol implementation
- TypeScript: For type safety and better developer experience
- Winston: For structured logging
Core Components
- ConsoleManager: Manages terminal sessions, input/output, and lifecycle
- ErrorDetector: Analyzes output for errors and exceptions
- MCP Server: Exposes console functionality through MCP tools
- Session Management: Handles multiple concurrent console sessions
Requirements
- Node.js >= 18.0.0
- Windows, macOS, or Linux operating system
- No additional build tools required!
Testing
Run the included test suite to verify functionality:
node test-functionality.js
Troubleshooting
Common Issues
- Permission denied errors: Ensure the server has permission to spawn processes
- node-pty compilation errors: Install build tools for your platform
- Session not responding: Check if the command requires TTY interaction
- Output not captured: Some applications may write directly to terminal, bypassing stdout
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
- Fork the repository
- Create your feature branch (
git checkout -b feature/AmazingFeature
) - Commit your changes (
git commit -m 'Add some AmazingFeature'
) - Push to the branch (
git push origin feature/AmazingFeature
) - Open a Pull Request
License
MIT License - see LICENSE file for details
Support
For issues, questions, or suggestions, please open an issue on GitHub: https://github.com/yourusername/mcp-console-automation/issues
Roadmap
- [ ] Add support for terminal recording and playback
- [ ] Implement session persistence and recovery
- [ ] Add more error detection patterns for specific languages
- [ ] Support for terminal multiplexing (tmux/screen integration)
- [ ] Web-based terminal viewer
- [ ] Session sharing and collaboration features
- [ ] Performance profiling tools
- [ ] Integration with popular CI/CD systems
Recommended Servers
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.
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.
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.

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

E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
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.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.