Irmu

What Irmu does

Irmu exposes web data collection capabilities through an MCP server. Its underlying web scraping API is designed to retrieve pages, render their contents, handle access barriers, and produce screenshots. This makes it suitable for agent workflows that need more than a basic HTTP fetch.

The service also covers higher-level extraction and answer retrieval. Agents can use AI extraction to turn page content into usable data, request answers from ChatGPT and Google AI Overview, and obtain structured information from services such as Booking.com.

These capabilities place Irmu in the search and data extraction category. It is relevant when an application needs to combine page retrieval with browser-oriented processing, visual captures, answer-engine results, or structured output from a particular web service.

How it works

Irmu presents the web scraping API through MCP so an AI client can use its web collection functions in an agent workflow. Requests may target several stages of the collection process: fetching a page, rendering it, applying a browser recipe, taking a screenshot, or extracting information with AI.

The same interface can be used for answer-oriented tasks involving ChatGPT or Google AI Overview. For site-specific data work, Irmu can return structured data from services such as Booking.com. The available capability therefore spans raw page acquisition, browser-assisted access, visual output, semantic extraction, and structured results.

Tools and capabilities

• Fetch web pages through the scraping API.
• Render pages before processing their contents.
• Handle web access that requires unblocking.
• Capture screenshots of web pages.
• Run browser recipes for repeatable browser actions.
• Extract information with AI.
• Retrieve ChatGPT and Google AI Overview answers.
• Return structured data from services such as Booking.com.

Irmu is a candidate for agents that need to inspect rendered web experiences rather than only download markup. Screenshot support can provide visual page output, while browser recipes address workflows that require browser-oriented handling. AI extraction and structured results are useful when downstream code needs organized information instead of an entire page.

The service can also support research flows that compare ordinary web content with answers produced by ChatGPT or Google AI Overview. Its capabilities cover both general web scraping and targeted extraction from named services, allowing a workflow to select the result type that fits the task.