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A Model Context Protocol server for Scrapezy that enables AI models to extract structured data from websites.
Scrapezy is an MCP server entry in ChatHome Skills, sourced from Docker MCP Registry and scored 100/100. As a Model Context Protocol server, it exposes tools that MCP-compatible LLM clients such as Claude, Cursor, and Copilot can call directly, extending an agent's reach beyond its built-in capabilities. ChatHome Skills discovered this entry through its daily ingest of official registries and GitHub discovery queries, and re-verifies repository facts, freshness signals, and install metadata on every run. The quality score weighs official-registry presence, a working install command, license clarity, GitHub star trajectory, and repository freshness — the full formula is on the Sources page. The install command above is ready to copy. Review the last-pushed date and repository status before adding Scrapezy to a production agent workflow; the snapshot facts below are point-in-time values from the most recent ingest.
docker run -i --rm mcp/scrapezyReview the upstream source before running this command.
{
"raw": "name: scrapezy\nimage: mcp/scrapezy\ntype: server\nmeta:\n category: devops\n tags:\n - scrapezy\n - devops\nabout:\n title: Scrapezy\n description: A Model Context Protocol server for Scrapezy that enables AI models to extract structured data from websites.\n icon: https://avatars.githubusercontent.com/u/196929482?s=200&v=4\nsource:\n project: https://github.com/Scrapezy/mcp\n commit: a8d31506d1f962c384840773e1918a310ec17032\nconfig:\n secrets:\n - name: scrapezy.auth_token\n env: SCRAPEZY_API_KEY\n example: your_api_key\n",
"path": "servers/scrapezy/server.yaml"
}