MCP Servers

AI Process Manager

Enables AI agents to query Windows process, window, and console information via structured JSON instead of screenshots, reducing token usage by 94-98%.

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README

AI Process Manager — MCP Server

Structured Windows state for AI agents — no screenshots.

This MCP server exposes the AI Process Manager local HTTP API as tools for Claude Desktop, Cursor, and any MCP client. Instead of capturing pixels (~2,765 tokens per 1080p screenshot), agents read JSON and text (~15–150 tokens per query) from processes, windows, consoles, and UI Automation trees.

Requires: AIProcessManager.exe running on Windows (system tray). Node.js ≥ 14. Zero npm dependencies.

Why this exists

Computer-use agents often "look" at the desktop via screenshots. That is slow (3–5 s), expensive in tokens, and sends pixel data through the model. AIPM answers structured questions on loopback:

Question	Screenshot	AIPM tool
Is the render still running?	~2,765 tokens	`check_process` → ~15 tokens
What's the console output?	screenshot + OCR	`read_window` → ~30 tokens
Did the export finish?	poll + screenshots	`wait_for(file_stable=...)` → one call

Measured on a real machine: ~94–98% fewer perception tokens per action vs screenshots.

Quick start

1. Start the backend

Ensure AIProcessManager.exe is running in your system tray.

2. Configure your MCP client

Claude Desktop — claude_desktop_config.json:

{
  "mcpServers": {
    "ai-process-manager": {
      "command": "node",
      "args": ["C:\\path\\to\\ai-process-manager\\mcp\\server.js"]
    }
  }
}

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