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HeartLoveLung

Scrapegraphai_MCP

by HeartLoveLung
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Python
Local

Scrapegraphai MCP

A local stdio MCP server for structured web scraping with ScrapeGraphAI and an OpenAI-compatible model API.

Tools

  • list_models: List models from the configured OpenAI-compatible API.

  • scrape_url: Scrape a URL with ScrapeGraphAI SmartScraperGraph and return extracted results.

Related MCP server: ISIS MCP

Requirements

  • Python 3.12+

  • Playwright Chromium

  • An OpenAI-compatible API key and base URL

Install

git clone https://github.com/HeartLoveLung/Scrapegraphai_MCP.git
cd Scrapegraphai_MCP

python -m venv .venv
.\.venv\Scripts\pip install -r requirements.txt
.\.venv\Scripts\playwright install chromium

You can also install dependencies manually:

.\.venv\Scripts\pip install scrapegraphai langchain-openai httpx requests python-dotenv playwright
.\.venv\Scripts\playwright install chromium

Environment

Copy the example file:

Copy-Item .env.example .env

Edit .env:

SCRAPEGRAPHAI_API_KEY=sk-your-api-key
SCRAPEGRAPHAI_BASE_URL=https://gpt.qt.cool/v1
SCRAPEGRAPHAI_MODEL=deepseek-v4-flash
SCRAPEGRAPHAI_VERIFY_SSL=false
SCRAPEGRAPHAI_MODEL_TOKENS=50000

Do not commit .env.

MCP Client Config

Copy mcp_config.example.json, replace the paths with your local repository path, and add it to an MCP-compatible client.

Windows example:

{
  "mcpServers": {
    "scrapegraphai-local": {
      "command": "C:\\path\\to\\Scrapegraphai_MCP\\.venv\\Scripts\\python.exe",
      "args": [
        "C:\\path\\to\\Scrapegraphai_MCP\\tools\\scrapegraphai_mcp_server.py"
      ],
      "env": {
        "SCRAPEGRAPHAI_API_KEY": "sk-your-api-key",
        "SCRAPEGRAPHAI_BASE_URL": "https://gpt.qt.cool/v1",
        "SCRAPEGRAPHAI_MODEL": "deepseek-v4-flash",
        "SCRAPEGRAPHAI_VERIFY_SSL": "false",
        "SCRAPEGRAPHAI_MODEL_TOKENS": "50000"
      }
    }
  }
}

You can also omit env from the MCP config and use a local .env file in the repository root.

Example Tool Calls

list_models

{
  "name": "list_models",
  "arguments": {
    "timeout": 10
  }
}

scrape_url

{
  "name": "scrape_url",
  "arguments": {
    "url": "https://gpt.qt.cool/checkin",
    "prompt": "Extract the main visible content and return JSON.",
    "model": "deepseek-v4-flash",
    "timeout": 90,
    "headless": true,
    "html_mode": true
  }
}

Local Smoke Test

Check that the server imports and exposes tools:

.\.venv\Scripts\python.exe -c "import importlib.util; spec=importlib.util.spec_from_file_location('m', r'tools\scrapegraphai_mcp_server.py'); m=importlib.util.module_from_spec(spec); spec.loader.exec_module(m); print(sorted(m.TOOLS.keys()))"

Expected output:

['list_models', 'scrape_url']

Notes

  • scrape_url starts a Playwright browser. Some sandboxed environments must allow Chromium process launch.

  • If the model API returns 503 model_unavailable, switch to another available model or retry later.

  • Replace all example API keys with your own key.

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