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Give AI agents controlled proxy web access, rendering, and structured extraction.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "proxyclaw-mcp-py" yet — see the docs or source repo.
Use proxyclaw-mcp-py to visit 10 competitor product pages, enable browser rendering, extract the product name, price, key selling points, and CTA button text from each page, and return structured JSON.
Structured JSON with key fields from each page for downstream competitor analysis.
Use proxyclaw-mcp-py to open a JavaScript-rendered news page, wait until the main content loads, then extract the headline, publish date, article summary, and author information.
Core content fields from the rendered page without missing dynamically loaded information.
Use proxyclaw-mcp-py to gather results for a target topic across supported sites, consistently extract the title, link, summary, source site, and timestamp, and compile them into tabular data.
A normalized dataset ready for research, monitoring, or reporting workflows.
Fetch URLs, run network-enabled CLI tools, and read generated files.
Let AI browse via your real Chrome for extraction and multi-step workflows.
Aggregate multiple MCP resource servers behind one HTTP endpoint.
Control a browser with AI for automation, extraction, interception, and screenshots.
Fetch, crawl, and search the web for AI agents in clean Markdown.
Control browsers, extract web data, and manage multi-browser tasks with natural language.