AI-first company: evidence on AI adoption

Ingested from the official MCP Registry

FastDrop pulled this entry from the official MCP Registry as company.ai-first/evidence and probed the endpoint. The maker did not submit it, so the outbound link is not endorsed and the description is not theirs.

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Tools this endpoint exposes

Read directly from the endpoint on 25 Oct 2026. Not supplied by the maker.

• start

  Start here for any question about adopting AI in a company: the map of the ai-first.company evidence. Returns the company cases by the kind of work AI was used for (customer service, legal work, offic

• open

  Open one part of the evidence map: a list (practices, cases, studies, figures, claim-checks, assessments) with filters such as theme, outcome, industry, company size, stage, priority, figure group (li

• get_evidence

  Get the full records for ids from the menus and lists (such as "case:klarna-ai-customer-service" or "claim-check:mit-95-percent-of-ai-pilots-fail"): figures, ratings, verdicts, caveats, primary source

• check_ai_figure

  Before quoting an AI statistic (e.g. '95% of AI pilots fail', 'only 13% of companies are ready for AI'), check where it comes from, who was asked and what it covers. Returns every claim check of a wid

• check_vendor_claim

  Check a claim made by an AI vendor or consultant, such as '30% productivity gain', 'cuts support costs by 40%' or 'our agents replace 700 staff'. Returns the questions to ask the vendor, the claim che

• review_ai_transformation_plan

  Review an AI transformation proposal, business case or rollout memo, for example before it goes to a board. Returns the do-first practices for the company’s size as a checklist, each with its evidence

• find_practices

  List practices for adopting AI that fit a company's size, rated by strength of evidence. Use it for 'Where should we start with AI?' or 'What should a 120-person manufacturer do first?'. Pass the numb

• find_company_cases

  List real companies that used AI and how it turned out: measured result, company-reported result, went wrong, or partly walked back. Use it for 'Who has done this?' or 'What went wrong for others?'. F