A Model Context Protocol (MCP) server for comfortable background process management on AI agents.
概览
A Model Context Protocol (MCP) server for comfortable background process management on AI agents. mcproc bridges the gap between AI agent development and traditional command-line workflows. It enables AI agents to manage long-running development processes (like dev servers, build watchers, etc.) while providing developers with full CLI access to monitor and control these same processes. Simple AI agent-launched processes are stateless and can't manage long-running processes effectively. mcproc solves this by: - : No more confusion about which agent or terminal is running what - all processes are centrally managed - : Logs are captured and stored, allowing AI agents to debug issues while reviewing logs from earlier - : Full CLI access means you're never locked out of your own development environment - 🔄 : Start and manage background processes from AI agents via MCP, then monitor them from your terminal - 👁️ : Processes started by AI agents are fully accessible via CLI and other...
README
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mcproc
A Model Context Protocol (MCP) server for comfortable background process management on AI agents.
Overview
mcproc bridges the gap between AI agent development and traditional command-line workflows. It enables AI agents to manage long-running development processes (like dev servers, build watchers, etc.) while providing developers with full CLI access to monitor and control these same processes.
Why mcproc?
Simple AI agent-launched processes are stateless and can’t manage long-running processes effectively. mcproc solves this by:
- Unified Control: No more confusion about which agent or terminal is running what - all processes are centrally managed
- Context Preservation: Logs are captured and stored, allowing AI agents to debug issues while reviewing logs from earlier
- Developer-Friendly: Full CLI access means you’re never locked out of your own development environment
Key Features
- 🔄 Unified Process Management: Start and manage background processes from AI agents via MCP, then monitor them from your terminal
- 👁️ Cross-Environment Visibility: Processes started by AI agents are fully accessible via CLI and other agents, and vice versa
- 📝 Intelligent Log Management: Capture, persist, and search process logs with powerful regex patterns
- 📁 Project-Aware: Automatically groups processes by project context
- 📊 Real-time Monitoring: Follow logs in real-time from CLI while AI agents manage the processes
- 🛡️ XDG Compliant: Follows XDG Base Directory specification for proper file organization
- ⚡ Wait-for-Log: Start processes and wait for specific log patterns to ensure readiness
- 🔍 Advanced Search: Time-based filtering, context lines, and regex support for log analysis
- 🧰 Toolchain Support: Execute commands through version managers (mise, asdf, nvm, rbenv, etc.)
- 🧹 Clean Command: Stop all processes in a project with a single command
- 🌲 Process Groups: Automatic cleanup of child processes when stopping parent processes
Installation
Using Homebrew (macOS and Linux)
# Add the tap
brew tap neptaco/tap
# Install mcproc
brew install mcproc
Build from source
Prerequisites
- Rust toolchain (rustc, cargo)
- protobuf compiler:
- macOS:
brew install protobuf - Linux:
apt-get install protobuf-compiler
- macOS:
git clone https://github.com/neptaco/mcproc.git
cd mcproc
cargo build --release
# Install to PATH (optional)
cargo install --path mcproc
Usage
Setup as MCP Server
After installing mcproc, you need to register it as an MCP server with your AI assistant.
For Claude Code
# Register mcproc as an MCP server
安装
This server does not publish a one-line install command.
Open the repository installation guide 新手?先看 mcpskill.org 教程 →配置
{
"mcpServers": {
"mcproc": {
"command": "mcproc",
"args": ["mcp", "serve"]
}
}
}