Google Flow Server

A Playwright-based automation pipeline for generating sports editorial graphic posters using Google Flow.

Project Architecture

newlab/
├── .gitignore
├── README.md
├── requirements.txt
├── main.py                   # Primary entry point
├── flow_scraper.py           # Legacy entry point wrapper
└── app/
    ├── __init__.py
    ├── config.py             # Configs, selectors, and directory paths
    ├── prompts.py            # FLOW_PROMPT text templates
    ├── utils/
    │   ├── __init__.py
    │   ├── clipboard.py      # Windows clipboard image copy helper
    │   └── image.py          # Directory image scanning logic
    └── automation/
        ├── __init__.py
        └── flow.py           # Playwright UI steps & automation pipeline

Prerequisites

• Python 3.10+
• Google Chrome browser
• Pre-configured chrome_profile/ directory logged into Google

Setup & Execution with UV

This project is configured to use uv for fast, isolated Python package and environment management.

1. Initialize / Install Dependencies

uv sync
uv run python -m playwright install chromium

2. Run FastMCP Server

To run the FastMCP server via STDIO (for Claude Desktop, Cursor, or MCP clients):

uv run python -m app.mcp.server

or using FastMCP CLI:

uv run fastmcp run app/mcp/server.py

3. Run MCP Inspector Mode

To launch the MCP Server with interactive web-based Inspector:

uv run fastmcp dev inspector app/mcp/server.py

or via npx:

npx @modelcontextprotocol/inspector uv run python -m app.mcp.server

4. Connect with Claude Desktop

Add the following block to your %APPDATA%\Claude\claude_desktop_config.json:

{
  "mcpServers": {
    "google-flow": {
      "command": "C:/Users/sohel/AppData/Roaming/Python/Python312/Scripts/uv.exe",
      "args": [
        "--directory",
        "c:/MCP Servers/flow-project",
        "run",
        "python",
        "-m",
        "app.mcp.server"
      ]
    }
  }
}

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Direct Script Execution

Execute standard automation pipeline via main.py:

uv run python main.py