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Example prompts for the EdgeComet MCP server ​

These prompts work in any AI client connected to the EdgeComet MCP server. Ask them in your own words: the agent turns each one into reports and queries, and EdgeComet computes the numbers.

Each prompt lists the sources it combines. The query guide shows the queries behind several of them.

One table for every indexable page ​

Give me every indexable page with its number of linking pages, last Googlebot visit, last AI bot visit, clicks and impressions, as a CSV.

Combines: Evergreen Crawl, bot requests, Search Console.

The agent joins the three sources on the URL and returns a download link from export. Sorted in a spreadsheet, the file shows pages that are linked but never fetched by Googlebot, and pages Googlebot fetches that earn no impressions.

Which URLs with Search Console impressions returned a 4xx or 5xx to bots in the last 30 days?

Combines: bot requests, Search Console.

Each row is a URL, the status code bots received, and how many times it happened. These are errors on pages that Google still shows to searchers.

Sitemap URLs Googlebot has not requested ​

Which URLs in my sitemap has Googlebot not requested in the last 30 days?

Combines: your XML sitemap, bot requests.

Useful after a launch or a migration, to see which listed pages Google has not come back for. The sitemap stores URLs in a lightly normalized form, and the agent checks a short result against the URL text before it reports a page as missing.

Pages close to page one, and how well they are linked ​

Which indexable pages average position 4 to 20 with at least 20 impressions, and how many pages link to each?

Combines: Evergreen Crawl, Search Console.

A page in striking distance with few linking pages is a candidate for new internal links. Follow up with the next prompt to find where they should come from.

Find five pages that should link to /log-analyzer/, with an anchor text for each, and draft the links as Edge SEO changes.

Combines: Evergreen Crawl, Search Console, the page's live markup.

find_pages ranks live, indexable pages on the same topic that do not link yet, says why each one matched and suggests anchor texts. The agent reads each page's markup, previews the inserted link and saves the drafts as one batch for you to review. See Edge SEO drafting.

What changed on pages that lost clicks ​

Which pages earned fewer clicks in this crawl than in the previous one, and did their title or internal links change?

Combines: two Evergreen Crawl snapshots, Search Console for each snapshot's window.

Each snapshot carries the clicks from its own window, which puts the drop and the change on one row: the old and new title, and the inlink count before and after.

Pages that lost indexability, and the release behind it ​

Which pages became noindex or non-canonical in the last 30 days? Group them by page type, and tell me if a release caused it.

Combines: the page change log, site releases.

The change log holds each change with its old and new value and when bots first saw it. list_releases names the deploys that made the same change across one template, with example pages. See Site releases.

Search and AI demand by section ​

Break down Googlebot visits, AI bot visits, AI user fetches and search clicks by top-level folder for the last 30 days.

Combines: bot requests, Search Console.

The agent derives the folder from each URL and groups by it, or groups by your saved segments. You see which sections AI assistants read on demand against the clicks Google sends them.

AI user fetches are the real-time requests an assistant makes while answering someone, such as ChatGPT-User or Claude-User. See AI crawler user agents EdgeComet identifies for the bot groups.

Performance by author, category or any extracted value ​

Which blog authors' articles earn the most clicks and impressions?

Combines: custom extraction, Search Console.

Any custom extraction field works as a grouping key. The same question works for a category, a brand, or a stock status that you extract from your pages.

Pages behind AI fan-out queries ​

Which pages show up for long, AI-style queries without getting clicks, and how often do AI assistants fetch those pages?

Combines: Search Console queries, bot requests.

Fan-out queries are the searches AI assistants, such as Google AI Mode and Gemini, run on Google while they answer a person. They draw impressions and almost never a click. See Fan-out queries.

The agent finds the pages those queries land on and lists the AI bot and AI user fetches each page received.

Redirects for retired URLs ​

These 150 old product URLs return 404. Plan a redirect for each one to the closest live page, and draft the redirects.

Combines: Evergreen Crawl, Search Console, bot requests.

map_redirects proposes a destination per URL: a similar live page or the nearest live parent. It lists the rows that need your call, and drafts one redirect rule per URL as a single Action Board task for you to review and deploy. See map_redirects.

Bots that fake their identity ​

Which bots are being spoofed on my site, and how many fake requests did each one make in the last 30 days?

Combines: bot requests, IP verification.

EdgeComet checks each request's IP address against the ranges the bot's operator publishes. The agent counts the requests that claimed a bot's name from outside those ranges, per bot.

Every other query leaves fake requests out by default, and they appear only when you ask about them. See How to verify Googlebot and AI bot IP addresses.

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