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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.
Proxy multiple MCP servers while reducing token usage with on-demand tool loading.
Proxy MCP to JSON-RPC for AI-driven 1C task, project, knowledge, and file management.
Fetch URLs, run network-enabled CLI tools, and read generated files.
Automate browser navigation, interaction, and web data extraction for online tasks.
Let AI browse via your real Chrome for extraction and multi-step workflows.
Give AI agents reliable web access with proxies and browser rendering.