{"$schema":"https://verifymcp.io/schemas/trust-report.json","schemaVersion":1,"license":{"name":"CC BY-NC 4.0","url":"https://creativecommons.org/licenses/by-nc/4.0/"},"generatedAt":"2026-11-05T15:56:39.625Z","url":"https://verifymcp.io/servers/company-ai-first-evidence/mcp","markdownUrl":"https://verifymcp.io/servers/company-ai-first-evidence/mcp.md","server":{"slug":"company-ai-first-evidence","name":"AI-first company: evidence on AI adoption","registryName":"company.ai-first/evidence","description":"Rated evidence on AI adoption: practices, company cases, claim checks and readiness assessments.","registryStatus":"active","deletedAt":null,"statusMessage":null,"liveness":"live","publisher":{"class":"unknown","claimed":false}},"component":{"slug":"mcp","type":"remote","identifier":"https://mcp.ai-first.company/mcp","withdrawn":false,"url":"https://verifymcp.io/servers/company-ai-first-evidence/mcp","version":"0.3.6","transport":null,"scoredAt":"2026-11-05T02:08:56.946Z"},"score":{"total":72,"tier":"medium","status":"scored","weekDelta":4,"history":[{"date":"2026-11-05","total":72},{"date":"2026-11-04","total":71},{"date":"2026-11-03","total":71},{"date":"2026-11-02","total":70},{"date":"2026-11-01","total":70},{"date":"2026-10-31","total":69},{"date":"2026-10-30","total":69},{"date":"2026-10-29","total":68},{"date":"2026-10-28","total":68},{"date":"2026-10-27","total":68},{"date":"2026-10-26","total":67},{"date":"2026-10-25","total":67}]},"categories":[{"name":"Endpoint Security","score":63,"verdict":"fail","reasons":["The endpoint's TLS certificate is valid, in date, and uses a strong key.","No authorisation is required to call this server. 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Returns the company cases by the kind of work AI was used for (customer service, legal work, office assistant and others), the six themes (with counts of practices, cases and studies), the claim checks of widely repeated AI statistics, the groups of other figures, the company cases by outcome, the assessments by kind, and what each filter value and rating means. Then open the part that fits and fetch records with get_evidence.","inputs":[],"outputs":[],"hasOutputSchema":false,"hasExamples":false,"tokenEstimate":115},{"name":"open","title":"Open one part of the evidence map","description":"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 (line) or assessment kind. Returns every matching row in one line with its id, or, when there are more than 25, a menu splitting them by the next filter, with counts. Use the arguments the menus show. Then fetch the rows you pick with get_evidence.","inputs":[{"name":"employees","type":"integer","required":false,"description":"Number of employees, e.g. 120."},{"name":"free_only","type":"boolean","required":false,"description":"Assessments only: free to use."},{"name":"industry","type":"string","required":false,"description":"Cases in this industry: professional-services, agencies, ecommerce-retail, manufacturing, or other (none of the four, e.g. banks, airlines, public bodies). Practices apply to all industries."},{"name":"kind","type":"string","required":false,"description":"Figures: the kind of number, e.g. measured-in-a-study or self-reported. Assessments: the kind key from start, e.g. readiness-surveys."},{"name":"line","type":"string","required":false,"description":"Figures only: the group key from start, e.g. time-freed or running-cost."},{"name":"list","type":"string","required":true,"description":"Which list: practices, cases, studies, figures, claim-checks or assessments."},{"name":"outcome","type":"string","required":false,"description":"Cases with this outcome: measured, company-reported, went-wrong or walked-back."},{"name":"priority","type":"string","required":false,"description":"Practices with this priority."},{"name":"size","type":"string","required":false,"description":"Company size band: micro-small, medium, mid-market, enterprise (1–49, 50–249, 250–999, 1,000+ employees). Or pass employees instead."},{"name":"stage","type":"string","required":false,"description":"How far the company is: explore, adopt, redesign or run."},{"name":"task","type":"string","required":false,"description":"Cases only: the kind of work AI was used for, a task key from start, e.g. customer-service-and-support or legal-research-drafting-and-filings."},{"name":"theme","type":"string","required":false,"description":"A theme key from start, e.g. governance-and-risk or people-and-skills."}],"outputs":[],"hasOutputSchema":false,"hasExamples":false,"tokenEstimate":443},{"name":"get_evidence","title":"Get full evidence records by id","description":"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 sources, the ai-first.company link, and the ids of related studies, cases and practices to follow. Up to 20 ids per call. Quote and cite only from what this returns.","inputs":[{"name":"ids","type":"array","required":true,"description":"Ids as the menus and lists give them, e.g. [\"case:klarna-ai-customer-service\", \"practice:ask-ai-vendors-for-proof\"]."}],"outputs":[],"hasOutputSchema":false,"hasExamples":false,"tokenEstimate":139},{"name":"check_ai_figure","title":"Check an AI statistic before quoting it","description":"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 widely repeated statistic and the groups of other figures; fetch the matching claim check, or open the group the figure belongs to. Use it for figures from surveys, reports and the press. For a claim a vendor makes about its own product, use check_vendor_claim.","inputs":[],"outputs":[],"hasOutputSchema":false,"hasExamples":false,"tokenEstimate":112},{"name":"check_vendor_claim","title":"Check a vendor’s AI claim","description":"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 checks, the groups of figures and the company cases by the kind of work AI was used for, so you can find the same result and companies that tried the same kind of tool. Use it whenever someone selling or proposing AI quotes a result. For a statistic from the press or a report, use check_ai_figure.","inputs":[],"outputs":[],"hasOutputSchema":false,"hasExamples":false,"tokenEstimate":120},{"name":"review_ai_transformation_plan","title":"Review an AI plan or business case","description":"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 rating and wording that may show it, and how to find similar cases. You read the plan and decide for each practice whether the plan commits to it, rules it out or leaves it out. Pass the size and industry; the plan itself stays with you. For one figure in the plan, use check_ai_figure.","inputs":[{"name":"employees","type":"integer","required":false,"description":"Number of employees, e.g. 120."},{"name":"industry","type":"string","required":false,"description":"The site’s industry category, if one fits: professional-services (consulting, accounting, audit, law), agencies (marketing, advertising, creative), ecommerce-retail (online shops, retail, wholesale),…"},{"name":"size","type":"string","required":false,"description":"Company size band: micro-small, medium, mid-market, enterprise (1–49, 50–249, 250–999, 1,000+ employees). Or pass employees instead."}],"outputs":[],"hasOutputSchema":false,"hasExamples":false,"tokenEstimate":259},{"name":"find_practices","title":"Find rated practices for adopting AI","description":"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 number of employees or a size band, and optionally the theme, stage or priority. Returns the practices in one line each, or a menu by theme when there are many; fetch the ones you use with get_evidence for their studies, cases and links.","inputs":[{"name":"employees","type":"integer","required":false,"description":"Number of employees, e.g. 120."},{"name":"priority","type":"string","required":false,"description":"Practices with this priority."},{"name":"size","type":"string","required":false,"description":"Company size band: micro-small, medium, mid-market, enterprise (1–49, 50–249, 250–999, 1,000+ employees). Or pass employees instead."},{"name":"stage","type":"string","required":false,"description":"How far the company is: explore, adopt, redesign or run."},{"name":"theme","type":"string","required":false,"description":"A theme key from start, e.g. governance-and-risk or people-and-skills."}],"outputs":[],"hasOutputSchema":false,"hasExamples":false,"tokenEstimate":222},{"name":"find_company_cases","title":"Find company cases of AI use","description":"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?'. Filter by the kind of work AI was used for (task), outcome, theme, industry or company size; returns the cases in one line each, or a menu with counts when there are many. Fetch the ones you use with get_evidence for the story, who produced the figures and the public sources.","inputs":[{"name":"employees","type":"integer","required":false,"description":"Number of employees, e.g. 120."},{"name":"industry","type":"string","required":false,"description":"Cases in this industry: professional-services, agencies, ecommerce-retail, manufacturing, or other (none of the four, e.g. banks, airlines, public bodies). Practices apply to all industries."},{"name":"outcome","type":"string","required":false,"description":"Cases with this outcome: measured, company-reported, went-wrong or walked-back."},{"name":"size","type":"string","required":false,"description":"Company size band: micro-small, medium, mid-market, enterprise (1–49, 50–249, 250–999, 1,000+ employees). Or pass employees instead."},{"name":"task","type":"string","required":false,"description":"The kind of work AI was used for: a task key from start, e.g. customer-service-and-support."},{"name":"theme","type":"string","required":false,"description":"A theme key from start, e.g. governance-and-risk or people-and-skills."}],"outputs":[],"hasOutputSchema":false,"hasExamples":false,"tokenEstimate":302},{"name":"find_readiness_assessment","title":"Find an AI readiness or literacy assessment","description":"List published questionnaires, tests and task maps to assess AI readiness, AI literacy, staff attitudes or which tasks suit AI, best tested first, optionally by kind or free to use. Fetch the ones that fit with get_evidence for how well each has been tested, who answers it, its length, licence and cost. For advice on what to do, use find_practices.","inputs":[{"name":"free_only","type":"boolean","required":false,"description":"Only assessments that are free to use."},{"name":"kind","type":"string","required":false,"description":"The kind key from start, e.g. readiness-surveys or ai-knowledge-tests-and-self-ratings."}],"outputs":[],"hasOutputSchema":false,"hasExamples":false,"tokenEstimate":131},{"name":"board_brief","title":"Prepare a board brief on AI adoption","description":"Prepare a one-page board brief on a question about AI adoption, from rated evidence only. Returns the company cases by the kind of work AI was used for, the themes (with practice counts for the company’s size), the claim checks and figure groups, and how to write the brief: open the cases for the work in question and one to three themes, fetch eight to twelve records and write from them. Use it when someone needs a summary for a board, an owner or an investment committee. 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