Scrapegraphai_MCP
Provides tools for structured web scraping using ScrapeGraphAI with an OpenAI-compatible API, enabling AI agents to extract data from websites via natural language prompts.
This server does not currently have a deployable release on Glama. Follow the repository's setup instructions to install and configure it for your MCP client, including any required credentials and local dependencies.
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 ScrapeGraphAISmartScraperGraphand return extracted results.
Related MCP server: crawl4ai-mcp-server
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 chromiumYou can also install dependencies manually:
.\.venv\Scripts\pip install scrapegraphai langchain-openai httpx requests python-dotenv playwright
.\.venv\Scripts\playwright install chromiumEnvironment
Copy the example file:
Copy-Item .env.example .envEdit .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=50000Do 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_urlstarts 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.
This server cannot be deployed
Maintenance
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