request_rescan. A customer’s own token lists more: 30 tools, or 39 when the account owner has turned on editing for the site’s connection. Those two counts come from the service source with the current release settings, not from a live customer token, so ask your assistant to list its tools to see your own. The extra tools are listed below. Every tool is scoped to the token you connect with, so no tool takes a url or domain parameter: the token decides which business the answers are about.
No account yet? Point your assistant at the demo endpoint (
https://areyoufoundbyai.com/mcp/demo) to try all 20 tools against our own live monitoring of areyoufoundbyai.com. No key and no signup. On the demo, request_rescan returns a worked example of its response and queues nothing.In Claude Code: claude mcp add --transport http found-by-ai https://areyoufoundbyai.com/mcp/demoget_crawler_access, get_ai_traffic, get_agent_view, get_benchmark, get_share_of_voice, get_cited_queries, get_source_profile, get_citation_sources, get_schema_evidence and get_regional_visibility) read saved measurements or existing caches only. They make no provider or browser call and consume no scan allowance. Missing or failed evidence stays unavailable, not zero. Quoted source text in their results is untrusted data.
The 20 tools on every monitor token and the demo
1. get_visibility
The latest AI Visibility and AI Readiness scores (each out of 100), with the previous week’s scores, the separate off-site Footprint score, and the subscores. Citability, E-E-A-T, technical, schema and platform compose Readiness; Footprint sits beside it, not inside it.
Being named in the answer prose counts in full toward your visibility score. A positive result recorded only as a list entry, citation or source title counts half. Older results without this distinction keep their recorded scoring basis. The AI Visibility score is an older weighted diagnostic score, not a percentage of AI recommendations.
Parameters: none.
2. get_question_trajectories
Every tracked buyer question with its measured history: how many of the 7 engines named the business on each measured day. Use it to see, question by question, where visibility is won or lost.
Parameters: none.
3. get_personas
The 2 to 4 buyer personas inferred from the business’s measured questions, described the way AI models would describe each buyer type, with the exact tracked questions each persona asks.
Parameters: none.
4. get_mentions
New pages on the web that mention the business, when a mention check has been run.
5. get_rivals
The competitor names the answer engines actually gave in the latest scan when they did not name this business.
Parameters: none.
6. get_cited_queries
Questions naming or citing a competitor: a reverse lookup over saved measurements. Give a competitor’s brand name or domain and get the buyer questions where the engines named them, which engines, how often, when they were last seen, and who else was named on those questions. It also reports where that domain was cited as a source. Coverage is the questions we have measured, so a thin result means we have not asked those questions yet, never that the competitor is absent from AI.
7. get_schema_evidence
The saved structured-data comparison: initial HTML against rendered JSON-LD, with read dates, incomplete states, excerpts and limitations. It reads stored evidence only and makes no provider request. Page through the findings with offset and limit.
8. get_regional_visibility
Saved regional naming observations: areas, buyer questions and engine naming observations, with retained samples and read coverage. Unknown and failed reads are kept distinct from “not named”. It makes no fresh provider requests.
Parameters: none.
9. get_answers
The exact answer each engine gave to each tracked buyer question in the latest deep measurement: engine, model, date, whether the business was named and on how many samples, live web search or model memory, the competitors named in that answer, the web searches the engine ran before answering (fan-out), and the question’s Google demand. This is the receipt behind every score.
How results are labelled. Named: your business is named in the answer. Cited: your website is linked in the answer’s sources. Listed: your name appears in a list, heading or source title rather than in the prose. Found via search: a page appears in recorded search results, which on its own is not a citation or recommendation. These can overlap. Unavailable is not a negative result.
10. get_share_of_voice
Saved share of voice, from saved measurements only. Two measurements, kept apart. First, your share of mentions in your own tracked answers against the rivals the engines named there. Second, web mention share: how often a web-scale index of ChatGPT answers mentions you against the brands we compare you with, which is not a rival list. Use get_rivals for who the engines name instead of you.
Parameters: none.
11. get_context
The complete weekly context document: scores, every tracked question with its verbatim answer status, mentions, and what to do next. It is the same content as the downloadable context.md, so an assistant can load the whole picture in one call.
Parameters: none.
12. get_fix_plan
The prioritised fix list from the latest deep scan: the specific changes that move the business up in AI answers, highest impact first.
Parameters: none.
13. get_citation_sources
Saved citation sources: the domains AI engines actually cite in answers matching this category, most-cited first, with whether this business appears on each.
Parameters: none.
14. get_crawler_access
Saved AI crawler access: whether the business’s robots.txt allows or blocks each documented AI crawler from OpenAI, Anthropic, Google, Perplexity, Apple, Microsoft, Meta and Common Crawl, split by what each one is for: search, model training, or fetching a page because a user asked. It reads stored evidence only, never a fresh fetch of robots.txt, and quotes the matching robots.txt rule for each.
It also names the vendors this checker cannot assess, so an agent does not read silence as permission.
Parameters: none.
15. get_source_profile
A saved profile of any domain the answer engines cite, from our measurement corpus: how often our measurements saw engines read it and across how many businesses and categories, what the site says it is (title and description from our crawl of its homepage), the co-read pack it travels in (sources the engines read together), and, where our crawler found one, the page where a business gets listed on it. A thin result means the engines rarely cite it in what we have measured so far.
16. get_post_brief
Everything an AI needs to draft social posts that move AI visibility, assembled from this week’s measured data: fresh third-party mentions to anchor on, the exact buyer questions the engines answer without naming the business (and who they name instead), the domains the engines actually read, and the entity rules that make a post retrievable. It returns a drafting brief, never generated copy: the drafting happens in your AI, in the business’s own voice.
Parameters: none.
17. get_ai_traffic
Saved AI-referred traffic: the visitors AI engines sent to the business’s site, as recorded by the site’s own beacon and already saved. It does not start a refresh.
18. get_agent_view
The saved agent-browser observation of the site: how a headless agent browser read it (full, partial or blank). A site that renders blank to agents is invisible to agentic AI regardless of content quality. It returns the saved observation and does not start a new read.
19. get_benchmark
The measured category benchmark, from saved measurements: where the business sits against every other measured business in its category: rank, percentile, and the distribution above and below.
Parameters: none.
20. request_rescan
The demo’s one action. It queues a fresh deep measurement now instead of waiting for the next scheduled scan, using one of the plan’s capped on-demand re-measures. It runs the measurement and changes nothing else. Results land in a few minutes; then read get_visibility again.
Parameters: none.
More tools on a customer token
The demo does not list any of these. The counts and names below come from the service source with the current release settings (token billing and the client workspace on). We have not listed them against a live customer token, so treat your own assistant’s tool list as the final word. Three saved-only reads, no parameters (23 with the 20 above):
Seven workspace reads (30 in total):
Nine workspace actions, listed only when the account owner has turned on editing for the site’s connection (39 in total). Each needs
confirmed: true, which records that the person agreed:
There is no schedule tool on the connection. You choose how often checks run (weekly, monthly or whenever you like) in your signed-in workspace.
Agency network catalogue
An agency connection (a network link or a per-staff scoped key) reaches a separate catalogue, served asfound-by-ai-fleet: the network tools below, plus saved-evidence reads for each permitted site. Each per-site tool takes a domain that must be one of the sites the connection can reach, as returned by list_sites.
Alongside those network tools, the catalogue carries saved-evidence reads for each permitted site, each taking
domain: get_site_crawler_access, get_site_ai_traffic, get_site_agent_view, get_site_benchmark, get_site_share_of_voice, get_site_cited_queries, get_site_source_profile, get_site_citation_sources, get_site_schema_evidence, get_site_regional_visibility, get_site_weekly_brief and get_site_grants. It also has get_balance (taking domain) for a site’s existing scan allowance, and the setup reads get_site_setup, get_edit_history and get_question_history. In the service source, the agency catalogue also carries the workspace tools above, each taking domain; the actions appear only for a connection allowed to make changes.
Per-staff keys are scoped and revocable. See Scoped keys.
Example prompts once connected
After adding the MCP server to your AI assistant, ask questions like these in plain language:Tool permissions at a glance
- Read tools (19 on the demo; on a customer token, also
get_balance,get_weekly_brief,get_grantsand the seven workspace reads):get_visibility,get_question_trajectories,get_personas,get_mentions,get_rivals,get_cited_queries,get_schema_evidence,get_regional_visibility,get_answers,get_share_of_voice,get_context,get_fix_plan,get_citation_sources,get_crawler_access,get_source_profile,get_post_brief,get_ai_traffic,get_agent_view,get_benchmark. - Action (1 on the demo):
request_rescan, which re-runs your own measurement inside your plan’s cap and touches nothing else. On a token account it queues nothing and points you to the workspace. - Workspace actions (9, only when the account owner has turned on editing):
quote_token_run,confirm_token_run,set_briefand the six report actions.
run_check is the action.
The MCP connection cannot change your plan or your billing settings. Without editing turned on, its only side effect is request_rescan. With editing on, confirm_token_run spends tokens from your shared balance, but only after the person has seen and agreed to the quoted price, and the brief and report actions save content in your workspace.