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
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。