What AI Agents Can Do
Connected AI agents can query scraped tables of any size, clean columns, export data, operate automations, and answer product questions from the docs.
Once connected over MCP, an AI assistant gets a focused set of capabilities over your cloud workspace, grouped into six areas. This page explains them by use case; the MCP tool reference lists every tool by name.
Understand your workspace
The agent can read your plan, credit balance, and its own access level — so it can answer "how many credits do I have left?" and warn you before starting anything expensive.
Work with your data
- Browse tables — list all result tables, grouped by the automation that produced them.
- Inspect — read a table's schema, row count, and a small sample.
- Query without limits — filter, aggregate, group, and sort tables server-side. The full table is never loaded into the AI's context, so a 100,000-row table is as easy to analyze as a 100-row one.
- Export — generate CSV, JSON, or Excel downloads, or send a table straight to Google Sheets.
Big-table safety
Large tables are never streamed into the conversation. The agent sees the schema plus a sample, then asks the server precise questions. Oversized responses are refused with a hint to narrow the query.
Clean your data
With a full-access token, agents can tidy tables the way you would by hand:
- Rename columns or change their type
- Delete irrelevant columns
- Merge 2–5 columns into one (street + city + zip → Address)
- Delete rows that match a filter — "drop every row with no price or image"
- Remove duplicate rows, keeping the first occurrence
Row deletion is never silent: the agent always gets the match count first and deletes only after you confirm.
Operate your automations
- List automations and their run history (available to every token, including read-only)
- Check a run's live progress
- Start or stop a run (full access)
This is what makes "re-run my competitor price scrape and put results in Sheets" a one-sentence job.
Start new extractions
Agents can create zero-configuration extractions — product data, emails, social links, phone numbers, and Google Maps places — from a list of URLs or from a column of an existing table. They can also discover the URLs for you — mapping a whole site from its sitemaps and turning "just the winter collection" into a URL table — and extract entire Shopify catalogues as clean per-variant product tables. This is powerful enough to get its own page.
Get product help
The agent has this documentation at its fingertips: it can search and read every docs page — the extension tools, the Cloud Platform, credits, guides — and answer questions from what the docs actually say, with a link to the right page.
Ask things like "how do I schedule a daily scrape?", "can the List Extractor handle infinite scroll?", or "what happens when I run out of credits?" and you get the concrete steps instead of a guess. Available to every token, including read-only.
Access levels
| Read-only token | Full-access token | |
|---|---|---|
| Read workspace info, tables, runs | ✔ | ✔ |
| Query & export tables | ✔ | ✔ |
| Search & read the product docs | ✔ | ✔ |
| Clean tables (rename/delete/merge columns) | — | ✔ |
| Delete rows & remove duplicates | — | ✔ |
| Start & stop runs | — | ✔ |
| Create new extractions | — | ✔ |
| Discover site URLs & extract Shopify stores | — | ✔ |
Choose read-only when you want an analyst; choose full access when you want an operator. Details in Security, and the full tool-by-tool list in the MCP tool reference.
Connect an AI Agent
Connect Claude, Claude Code, Cursor, or any MCP client to your Ultimate Web Scraper cloud workspace — guided setup for Claude, access tokens for other agents.
MCP Tool Reference
Every MCP tool a connected AI agent can use in Ultimate Web Scraper — querying tables, cleanup, exports, automations, site discovery, and Shopify extraction.