An AI model on its own is frozen in time. It knows what it was trained on and nothing since, which is why an agent asked about today's news, current prices or a niche topic will happily make something up. The fix is to give it live web data at the moment it answers, but raw web pages are a mess of navigation, ads and markup that waste tokens and confuse the model.
This tool is built for exactly that. You give it a search query or a URL, and it returns the top pages as clean, readable text with the clutter stripped out, ready to drop straight into a model's context. It is the retrieval step in retrieval-augmented generation, done for you. Here is how it works.
What you can pull
- Google results for any search query
- The top pages pulled back in full
- Clean, readable text with navigation and ads stripped
- Content structured for a language model to read
- The source URL for every page
Why AI agents need live web data
Retrieval-augmented generation, or RAG, is the pattern behind most useful AI tools: instead of relying on what the model memorised, you fetch relevant, current information and give it to the model to answer from. That grounding is what stops an agent inventing facts and lets it cite real sources. The hard part has always been the fetching, searching the web and turning messy HTML into clean text a model can actually use. This tool handles both steps in one call, so your agent gets grounded answers without you building a scraper.
How to pull web data with Tooltap
The RAG Web Browser takes a query or a URL and returns clean text.
- Give it a query or a URL. Enter a search term to pull the top matching pages, or a specific URL to fetch one page.
- Set how many results you want back for a search.
- Run it. Each page comes back as clean, readable text with the source URL.
- Use the text. Drop it into a model's context, store it for retrieval, or read it yourself.
- Or skip the copy-paste entirely and let your AI call it directly, covered next.
What people build with this
- Grounded chatbots. Give a support or research bot live web access so its answers are current and sourced, not guessed.
- Research agents. Let an agent search a topic, read the top pages and synthesise an answer with citations.
- Monitoring. Pull the latest pages on a topic, company or product on a schedule to keep a knowledge base fresh.
- Content workflows. Feed clean source material into a writing or summarising pipeline without hand-collecting it.
Doing this properly
The tool searches Google and retrieves public web pages, the same ones anyone can open in a browser, and returns them as clean text on your instruction. You are charged only for the pages that come back. Use the content within the terms of the sites you pull from and the rules that apply to you, especially if you republish anything rather than using it as context.
RAG Web Browser
Search Google and pull the top pages back as clean, LLM-ready text.