{"$schema":"https://wellknown.network/schemas/agent-record-v1.json","schemaVersion":"1","id":"ag_3zeejurb85xq","handle":"zrev-ai","url":"https://wellknown.network/agents/zrev-ai","links":{"self":"https://wellknown.network/agents/zrev-ai/record.json","html":"https://wellknown.network/agents/zrev-ai","markdown":"https://wellknown.network/agents/zrev-ai/record.md","api":"https://wellknown.network/api/v1/agents/zrev-ai","status":"https://wellknown.network/api/v1/agents/zrev-ai/status","claim":"https://wellknown.network/agents/zrev-ai/claim","claimApi":"https://wellknown.network/api/v1/claims","claimDescriptor":"https://wellknown.network/agents/zrev-ai/claim.json","badge":"https://wellknown.network/agents/zrev-ai/badge.svg","openapi":"https://wellknown.network/openapi.json","history":"https://wellknown.network/api/v1/agents/zrev-ai/history","tools":"https://wellknown.network/api/v1/agents/zrev-ai/tools"},"ard":{"identifier":"urn:air:go.zrev.ai:server:zrev-ai","type":"application/mcp-server-card+json"},"kind":"mcp_server","declared":{"name":"zRev AI","summary":"Grade any llms.txt, cold-read a homepage, run a B2B GTM ROI model, get a GTM diligence checklist.","description":"Grade any llms.txt, cold-read a homepage, run a B2B GTM ROI model, get a GTM diligence checklist.","publisher":{"name":"ai.zrev","url":null},"homepage":"https://www.zrev.ai/mcp","repository":null,"version":"1.0.0","license":null,"protocols":["mcp"],"tags":[],"pricing":null,"endpoints":[{"url":"https://go.zrev.ai/mcp","type":"mcp_streamable_http","auth":null,"probeable":true}],"skills":null,"tools":null,"extra":{"updatedAt":"2026-09-17T11:07:28.044899Z","publishedAt":"2026-09-17T11:07:28.044899Z","registryName":"ai.zrev/zrev"},"attribution":{"kind":"mcp_registry","name":"mcp_registry","summary":"mcp_registry","version":"mcp_registry","description":"mcp_registry","homepageUrl":"mcp_registry","publisherName":"mcp_registry"}},"derived":{"capabilities":[{"slug":"ai.evaluation","name":"Evaluation & Benchmarks","confidence":0.54,"provenance":"derived"},{"slug":"dev.ci-cd","name":"CI/CD & Deploy","confidence":0.525,"provenance":"derived"},{"slug":"productivity.crm","name":"CRM & Sales","confidence":0.525,"provenance":"derived"},{"slug":"commerce.pricing","name":"Pricing & Quotes","confidence":0.525,"provenance":"derived"},{"slug":"commerce.travel","name":"Travel & Booking","confidence":0.51,"provenance":"derived"}],"categories":["ai","commerce","dev","productivity"],"language":"en"},"observed":{"status":"live","statusReason":"Responded 4h ago.","lastOkAt":"2026-10-10T09:23:43.535Z","lastProbedAt":"2026-10-10T09:23:43.535Z","statusComputedAt":"2026-10-10T09:25:53.628Z","reliability30d":{"probes":81,"successRate":1,"p50Ms":19,"basis":"service","measures":{"availability":"availability","latency":"response time","tools":"tool surface observed","summary":"Checks reached the service itself."},"checks":{"total":81,"ok":81,"authBoundaryOk":0,"serviceOk":81,"note":"Counted from the observation rows for the window, checks of the server only (HTTP, A2A card, MCP initialize). ok = authBoundaryOk + serviceOk. `probes` is the sum of daily rollups and includes registry checks, so it can differ from `total`."}},"latestObservations":[{"at":"2026-10-10T09:23:43.535Z","kind":"mcp_initialize","ok":true,"httpStatus":200,"latencyMs":37,"error":null,"detail":{"tools":[{"name":"about_zrev","description":"Returns a plain-text profile of zRev AI: what the firm does, the companies it is the best fit for, who it is not for, its six service lines with a link to each,"},{"name":"get_benchmarks","description":"Returns zRev's typical engagement results as plain text: 2x pipeline velocity, 20% lower customer acquisition cost, 10 hours back per rep per week, 60% of GTM b"},{"name":"get_engagement_timeline","description":"Returns the phases of a standard 60-day zRev engagement as plain text: what happens in each phase, what is delivered, and when first results appear. Use when a "},{"name":"estimate_roi","description":"Runs zRev's ROI model on one company's numbers and returns, as plain text, the projected annual impact in USD split into pipeline lift, customer acquisition cos"},{"name":"grade_llms_txt","description":"Fetches https://<domain>/llms.txt (the file that tells AI systems what a site contains) and grades it with seven deterministic checks. Returns a 0 to 100 score "},{"name":"cold_read","description":"Fetches a company's public homepage and returns, in two or three sentences, what the company appears to do and who it serves, based only on the visible text of "},{"name":"gtm_diligence_checklist","description":"Returns zRev's go-to-market due diligence checklist for investors and acquirers: 47 questions across ten dimensions, each with the data-room artifact that answe"},{"name":"book_call","description":"Returns the link and instructions for booking a free 30-minute intro call with zRev's founder, plus what the call covers. It does not book anything: it only ret"},{"name":"leave_contact","description":"Records an email address, with optional name, company and note, so that zRev's founder can reach out, and returns a plain-text confirmation. This is the only to"}],"toolCount":9,"toolsHash":"838ac52e6cf8535c56c941d6753c0d96dd3e1ce73aeb90274be0a83220b477bf","serverName":"zrev","capabilities":["tools"],"serverVersion":"1.0.0","protocolVersion":"2025-06-18"}},{"at":"2026-10-10T02:29:16.107Z","kind":"mcp_initialize","ok":true,"httpStatus":200,"latencyMs":12,"error":null,"detail":{"tools":[{"name":"about_zrev","description":"Returns a plain-text profile of zRev AI: what the firm does, the companies it is the best fit for, who it is not for, its six service lines with a link to each,"},{"name":"get_benchmarks","description":"Returns zRev's typical engagement results as plain text: 2x pipeline velocity, 20% lower customer acquisition cost, 10 hours back per rep per week, 60% of GTM b"},{"name":"get_engagement_timeline","description":"Returns the phases of a standard 60-day zRev engagement as plain text: what happens in each phase, what is delivered, and when first results appear. Use when a "},{"name":"estimate_roi","description":"Runs zRev's ROI model on one company's numbers and returns, as plain text, the projected annual impact in USD split into pipeline lift, customer acquisition cos"},{"name":"grade_llms_txt","description":"Fetches https://<domain>/llms.txt (the file that tells AI systems what a site contains) and grades it with seven deterministic checks. Returns a 0 to 100 score "},{"name":"cold_read","description":"Fetches a company's public homepage and returns, in two or three sentences, what the company appears to do and who it serves, based only on the visible text of "},{"name":"gtm_diligence_checklist","description":"Returns zRev's go-to-market due diligence checklist for investors and acquirers: 47 questions across ten dimensions, each with the data-room artifact that answe"},{"name":"book_call","description":"Returns the link and instructions for booking a free 30-minute intro call with zRev's founder, plus what the call covers. It does not book anything: it only ret"},{"name":"leave_contact","description":"Records an email address, with optional name, company and note, so that zRev's founder can reach out, and returns a plain-text confirmation. This is the only to"}],"toolCount":9,"toolsHash":"838ac52e6cf8535c56c941d6753c0d96dd3e1ce73aeb90274be0a83220b477bf","serverName":"zrev","capabilities":["tools"],"serverVersion":"1.0.0","protocolVersion":"2025-06-18"}},{"at":"2026-10-09T19:26:25.181Z","kind":"mcp_initialize","ok":true,"httpStatus":200,"latencyMs":32,"error":null,"detail":{"tools":[{"name":"about_zrev","description":"Returns a plain-text profile of zRev AI: what the firm does, the companies it is the best fit for, who it is not for, its six service lines with a link to each,"},{"name":"get_benchmarks","description":"Returns zRev's typical engagement results as plain text: 2x pipeline velocity, 20% lower customer acquisition cost, 10 hours back per rep per week, 60% of GTM b"},{"name":"get_engagement_timeline","description":"Returns the phases of a standard 60-day zRev engagement as plain text: what happens in each phase, what is delivered, and when first results appear. Use when a "},{"name":"estimate_roi","description":"Runs zRev's ROI model on one company's numbers and returns, as plain text, the projected annual impact in USD split into pipeline lift, customer acquisition cos"},{"name":"grade_llms_txt","description":"Fetches https://<domain>/llms.txt (the file that tells AI systems what a site contains) and grades it with seven deterministic checks. Returns a 0 to 100 score "},{"name":"cold_read","description":"Fetches a company's public homepage and returns, in two or three sentences, what the company appears to do and who it serves, based only on the visible text of "},{"name":"gtm_diligence_checklist","description":"Returns zRev's go-to-market due diligence checklist for investors and acquirers: 47 questions across ten dimensions, each with the data-room artifact that answe"},{"name":"book_call","description":"Returns the link and instructions for booking a free 30-minute intro call with zRev's founder, plus what the call covers. It does not book anything: it only ret"},{"name":"leave_contact","description":"Records an email address, with optional name, company and note, so that zRev's founder can reach out, and returns a plain-text confirmation. This is the only to"}],"toolCount":9,"toolsHash":"838ac52e6cf8535c56c941d6753c0d96dd3e1ce73aeb90274be0a83220b477bf","serverName":"zrev","capabilities":["tools"],"serverVersion":"1.0.0","protocolVersion":"2025-06-18"}},{"at":"2026-10-09T12:27:55.648Z","kind":"mcp_initialize","ok":true,"httpStatus":200,"latencyMs":161,"error":null,"detail":{"tools":[{"name":"about_zrev","description":"Returns a plain-text profile of zRev AI: what the firm does, the companies it is the best fit for, who it is not for, its six service lines with a link to each,"},{"name":"get_benchmarks","description":"Returns zRev's typical engagement results as plain text: 2x pipeline velocity, 20% lower customer acquisition cost, 10 hours back per rep per week, 60% of GTM b"},{"name":"get_engagement_timeline","description":"Returns the phases of a standard 60-day zRev engagement as plain text: what happens in each phase, what is delivered, and when first results appear. Use when a "},{"name":"estimate_roi","description":"Runs zRev's ROI model on one company's numbers and returns, as plain text, the projected annual impact in USD split into pipeline lift, customer acquisition cos"},{"name":"grade_llms_txt","description":"Fetches https://<domain>/llms.txt (the file that tells AI systems what a site contains) and grades it with seven deterministic checks. Returns a 0 to 100 score "},{"name":"cold_read","description":"Fetches a company's public homepage and returns, in two or three sentences, what the company appears to do and who it serves, based only on the visible text of "},{"name":"gtm_diligence_checklist","description":"Returns zRev's go-to-market due diligence checklist for investors and acquirers: 47 questions across ten dimensions, each with the data-room artifact that answe"},{"name":"book_call","description":"Returns the link and instructions for booking a free 30-minute intro call with zRev's founder, plus what the call covers. It does not book anything: it only ret"},{"name":"leave_contact","description":"Records an email address, with optional name, company and note, so that zRev's founder can reach out, and returns a plain-text confirmation. This is the only to"}],"toolCount":9,"toolsHash":"838ac52e6cf8535c56c941d6753c0d96dd3e1ce73aeb90274be0a83220b477bf","serverName":"zrev","capabilities":["tools"],"serverVersion":"1.0.0","protocolVersion":"2025-06-18"}},{"at":"2026-10-09T05:25:30.281Z","kind":"mcp_initialize","ok":true,"httpStatus":200,"latencyMs":16,"error":null,"detail":{"tools":[{"name":"about_zrev","description":"Returns a plain-text profile of zRev AI: what the firm does, the companies it is the best fit for, who it is not for, its six service lines with a link to each,"},{"name":"get_benchmarks","description":"Returns zRev's typical engagement results as plain text: 2x pipeline velocity, 20% lower customer acquisition cost, 10 hours back per rep per week, 60% of GTM b"},{"name":"get_engagement_timeline","description":"Returns the phases of a standard 60-day zRev engagement as plain text: what happens in each phase, what is delivered, and when first results appear. Use when a "},{"name":"estimate_roi","description":"Runs zRev's ROI model on one company's numbers and returns, as plain text, the projected annual impact in USD split into pipeline lift, customer acquisition cos"},{"name":"grade_llms_txt","description":"Fetches https://<domain>/llms.txt (the file that tells AI systems what a site contains) and grades it with seven deterministic checks. Returns a 0 to 100 score "},{"name":"cold_read","description":"Fetches a company's public homepage and returns, in two or three sentences, what the company appears to do and who it serves, based only on the visible text of "},{"name":"gtm_diligence_checklist","description":"Returns zRev's go-to-market due diligence checklist for investors and acquirers: 47 questions across ten dimensions, each with the data-room artifact that answe"},{"name":"book_call","description":"Returns the link and instructions for booking a free 30-minute intro call with zRev's founder, plus what the call covers. It does not book anything: it only ret"},{"name":"leave_contact","description":"Records an email address, with optional name, company and note, so that zRev's founder can reach out, and returns a plain-text confirmation. This is the only to"}],"toolCount":9,"toolsHash":"838ac52e6cf8535c56c941d6753c0d96dd3e1ce73aeb90274be0a83220b477bf","serverName":"zrev","capabilities":["tools"],"serverVersion":"1.0.0","protocolVersion":"2025-06-18"}},{"at":"2026-10-08T22:23:47.959Z","kind":"mcp_initialize","ok":true,"httpStatus":200,"latencyMs":12,"error":null,"detail":{"tools":[{"name":"about_zrev","description":"Returns a plain-text profile of zRev AI: what the firm does, the companies it is the best fit for, who it is not for, its six service lines with a link to each,"},{"name":"get_benchmarks","description":"Returns zRev's typical engagement results as plain text: 2x pipeline velocity, 20% lower customer acquisition cost, 10 hours back per rep per week, 60% of GTM b"},{"name":"get_engagement_timeline","description":"Returns the phases of a standard 60-day zRev engagement as plain text: what happens in each phase, what is delivered, and when first results appear. Use when a "},{"name":"estimate_roi","description":"Runs zRev's ROI model on one company's numbers and returns, as plain text, the projected annual impact in USD split into pipeline lift, customer acquisition cos"},{"name":"grade_llms_txt","description":"Fetches https://<domain>/llms.txt (the file that tells AI systems what a site contains) and grades it with seven deterministic checks. Returns a 0 to 100 score "},{"name":"cold_read","description":"Fetches a company's public homepage and returns, in two or three sentences, what the company appears to do and who it serves, based only on the visible text of "},{"name":"gtm_diligence_checklist","description":"Returns zRev's go-to-market due diligence checklist for investors and acquirers: 47 questions across ten dimensions, each with the data-room artifact that answe"},{"name":"book_call","description":"Returns the link and instructions for booking a free 30-minute intro call with zRev's founder, plus what the call covers. It does not book anything: it only ret"},{"name":"leave_contact","description":"Records an email address, with optional name, company and note, so that zRev's founder can reach out, and returns a plain-text confirmation. This is the only to"}],"toolCount":9,"toolsHash":"838ac52e6cf8535c56c941d6753c0d96dd3e1ce73aeb90274be0a83220b477bf","serverName":"zrev","capabilities":["tools"],"serverVersion":"1.0.0","protocolVersion":"2025-06-18"}},{"at":"2026-10-08T15:23:33.169Z","kind":"mcp_initialize","ok":true,"httpStatus":200,"latencyMs":39,"error":null,"detail":{"tools":[{"name":"about_zrev","description":"Returns a plain-text profile of zRev AI: what the firm does, the companies it is the best fit for, who it is not for, its six service lines with a link to each,"},{"name":"get_benchmarks","description":"Returns zRev's typical engagement results as plain text: 2x pipeline velocity, 20% lower customer acquisition cost, 10 hours back per rep per week, 60% of GTM b"},{"name":"get_engagement_timeline","description":"Returns the phases of a standard 60-day zRev engagement as plain text: what happens in each phase, what is delivered, and when first results appear. Use when a "},{"name":"estimate_roi","description":"Runs zRev's ROI model on one company's numbers and returns, as plain text, the projected annual impact in USD split into pipeline lift, customer acquisition cos"},{"name":"grade_llms_txt","description":"Fetches https://<domain>/llms.txt (the file that tells AI systems what a site contains) and grades it with seven deterministic checks. Returns a 0 to 100 score "},{"name":"cold_read","description":"Fetches a company's public homepage and returns, in two or three sentences, what the company appears to do and who it serves, based only on the visible text of "},{"name":"gtm_diligence_checklist","description":"Returns zRev's go-to-market due diligence checklist for investors and acquirers: 47 questions across ten dimensions, each with the data-room artifact that answe"},{"name":"book_call","description":"Returns the link and instructions for booking a free 30-minute intro call with zRev's founder, plus what the call covers. It does not book anything: it only ret"},{"name":"leave_contact","description":"Records an email address, with optional name, company and note, so that zRev's founder can reach out, and returns a plain-text confirmation. This is the only to"}],"toolCount":9,"toolsHash":"838ac52e6cf8535c56c941d6753c0d96dd3e1ce73aeb90274be0a83220b477bf","serverName":"zrev","capabilities":["tools"],"serverVersion":"1.0.0","protocolVersion":"2025-06-18"}},{"at":"2026-10-08T09:22:42.786Z","kind":"mcp_initialize","ok":true,"httpStatus":200,"latencyMs":100,"error":null,"detail":{"tools":[{"name":"about_zrev","description":"Returns a plain-text profile of zRev AI: what the firm does, the companies it is the best fit for, who it is not for, its six service lines with a link to each,"},{"name":"get_benchmarks","description":"Returns zRev's typical engagement results as plain text: 2x pipeline velocity, 20% lower customer acquisition cost, 10 hours back per rep per week, 60% of GTM b"},{"name":"get_engagement_timeline","description":"Returns the phases of a standard 60-day zRev engagement as plain text: what happens in each phase, what is delivered, and when first results appear. Use when a "},{"name":"estimate_roi","description":"Runs zRev's ROI model on one company's numbers and returns, as plain text, the projected annual impact in USD split into pipeline lift, customer acquisition cos"},{"name":"grade_llms_txt","description":"Fetches https://<domain>/llms.txt (the file that tells AI systems what a site contains) and grades it with seven deterministic checks. Returns a 0 to 100 score "},{"name":"cold_read","description":"Fetches a company's public homepage and returns, in two or three sentences, what the company appears to do and who it serves, based only on the visible text of "},{"name":"gtm_diligence_checklist","description":"Returns zRev's go-to-market due diligence checklist for investors and acquirers: 47 questions across ten dimensions, each with the data-room artifact that answe"},{"name":"book_call","description":"Returns the link and instructions for booking a free 30-minute intro call with zRev's founder, plus what the call covers. It does not book anything: it only ret"},{"name":"leave_contact","description":"Records an email address, with optional name, company and note, so that zRev's founder can reach out, and returns a plain-text confirmation. This is the only to"}],"toolCount":9,"toolsHash":"838ac52e6cf8535c56c941d6753c0d96dd3e1ce73aeb90274be0a83220b477bf","serverName":"zrev","capabilities":["tools"],"serverVersion":"1.0.0","protocolVersion":"2025-06-18"}},{"at":"2026-10-08T02:21:53.180Z","kind":"mcp_initialize","ok":true,"httpStatus":200,"latencyMs":13,"error":null,"detail":{"tools":[{"name":"about_zrev","description":"Returns a plain-text profile of zRev AI: what the firm does, the companies it is the best fit for, who it is not for, its six service lines with a link to each,"},{"name":"get_benchmarks","description":"Returns zRev's typical engagement results as plain text: 2x pipeline velocity, 20% lower customer acquisition cost, 10 hours back per rep per week, 60% of GTM b"},{"name":"get_engagement_timeline","description":"Returns the phases of a standard 60-day zRev engagement as plain text: what happens in each phase, what is delivered, and when first results appear. Use when a "},{"name":"estimate_roi","description":"Runs zRev's ROI model on one company's numbers and returns, as plain text, the projected annual impact in USD split into pipeline lift, customer acquisition cos"},{"name":"grade_llms_txt","description":"Fetches https://<domain>/llms.txt (the file that tells AI systems what a site contains) and grades it with seven deterministic checks. Returns a 0 to 100 score "},{"name":"cold_read","description":"Fetches a company's public homepage and returns, in two or three sentences, what the company appears to do and who it serves, based only on the visible text of "},{"name":"gtm_diligence_checklist","description":"Returns zRev's go-to-market due diligence checklist for investors and acquirers: 47 questions across ten dimensions, each with the data-room artifact that answe"},{"name":"book_call","description":"Returns the link and instructions for booking a free 30-minute intro call with zRev's founder, plus what the call covers. It does not book anything: it only ret"},{"name":"leave_contact","description":"Records an email address, with optional name, company and note, so that zRev's founder can reach out, and returns a plain-text confirmation. This is the only to"}],"toolCount":9,"toolsHash":"838ac52e6cf8535c56c941d6753c0d96dd3e1ce73aeb90274be0a83220b477bf","serverName":"zrev","capabilities":["tools"],"serverVersion":"1.0.0","protocolVersion":"2025-06-18"}},{"at":"2026-10-07T19:25:15.431Z","kind":"mcp_initialize","ok":true,"httpStatus":200,"latencyMs":14,"error":null,"detail":{"tools":[{"name":"about_zrev","description":"Returns a plain-text profile of zRev AI: what the firm does, the companies it is the best fit for, who it is not for, its six service lines with a link to each,"},{"name":"get_benchmarks","description":"Returns zRev's typical engagement results as plain text: 2x pipeline velocity, 20% lower customer acquisition cost, 10 hours back per rep per week, 60% of GTM b"},{"name":"get_engagement_timeline","description":"Returns the phases of a standard 60-day zRev engagement as plain text: what happens in each phase, what is delivered, and when first results appear. Use when a "},{"name":"estimate_roi","description":"Runs zRev's ROI model on one company's numbers and returns, as plain text, the projected annual impact in USD split into pipeline lift, customer acquisition cos"},{"name":"grade_llms_txt","description":"Fetches https://<domain>/llms.txt (the file that tells AI systems what a site contains) and grades it with seven deterministic checks. Returns a 0 to 100 score "},{"name":"cold_read","description":"Fetches a company's public homepage and returns, in two or three sentences, what the company appears to do and who it serves, based only on the visible text of "},{"name":"gtm_diligence_checklist","description":"Returns zRev's go-to-market due diligence checklist for investors and acquirers: 47 questions across ten dimensions, each with the data-room artifact that answe"},{"name":"book_call","description":"Returns the link and instructions for booking a free 30-minute intro call with zRev's founder, plus what the call covers. It does not book anything: it only ret"},{"name":"leave_contact","description":"Records an email address, with optional name, company and note, so that zRev's founder can reach out, and returns a plain-text confirmation. This is the only to"}],"toolCount":9,"toolsHash":"838ac52e6cf8535c56c941d6753c0d96dd3e1ce73aeb90274be0a83220b477bf","serverName":"zrev","capabilities":["tools"],"serverVersion":"1.0.0","protocolVersion":"2025-06-18"}}],"tools":[{"name":"about_zrev","description":"Returns a plain-text profile of zRev AI: what the firm does, the companies it is the best fit for, who it is not for, its six service lines with a link to each,"},{"name":"get_benchmarks","description":"Returns zRev's typical engagement results as plain text: 2x pipeline velocity, 20% lower customer acquisition cost, 10 hours back per rep per week, 60% of GTM b"},{"name":"get_engagement_timeline","description":"Returns the phases of a standard 60-day zRev engagement as plain text: what happens in each phase, what is delivered, and when first results appear. Use when a "},{"name":"estimate_roi","description":"Runs zRev's ROI model on one company's numbers and returns, as plain text, the projected annual impact in USD split into pipeline lift, customer acquisition cos"},{"name":"grade_llms_txt","description":"Fetches https://<domain>/llms.txt (the file that tells AI systems what a site contains) and grades it with seven deterministic checks. Returns a 0 to 100 score "},{"name":"cold_read","description":"Fetches a company's public homepage and returns, in two or three sentences, what the company appears to do and who it serves, based only on the visible text of "},{"name":"gtm_diligence_checklist","description":"Returns zRev's go-to-market due diligence checklist for investors and acquirers: 47 questions across ten dimensions, each with the data-room artifact that answe"},{"name":"book_call","description":"Returns the link and instructions for booking a free 30-minute intro call with zRev's founder, plus what the call covers. It does not book anything: it only ret"},{"name":"leave_contact","description":"Records an email address, with optional name, company and note, so that zRev's founder can reach out, and returns a plain-text confirmation. This is the only to"}],"package":null,"toolSurface":{"id":"ts_xm694ep7nemx","endpointId":"ep_cfdvm4epufdg","hash":"838ac52e6cf8535c56c941d6753c0d96dd3e1ce73aeb90274be0a83220b477bf","toolCount":9,"serverName":"zrev","serverVersion":"1.0.0","protocolVersion":"2025-06-18","firstSeenAt":"2026-09-28T12:26:16.808Z","lastSeenAt":"2026-10-10T09:23:43.597Z","observations":44,"toolNames":["about_zrev","get_benchmarks","get_engagement_timeline","estimate_roi","grade_llms_txt","cold_read","gtm_diligence_checklist","book_call","leave_contact"],"distinctSurfaces":2},"endpointFacts":[{"id":"ep_cfdvm4epufdg","url":"https://go.zrev.ai/mcp","type":"mcp_streamable_http","factsCheckedAt":"2026-10-09T12:27:55.658Z","auth":{"observedAt":"2026-10-09T12:27:55.831Z","authRequired":false,"scheme":null,"resourceMetadata":null,"authorizationServer":null,"conformance":{"dpop":false,"rfc8414":false,"rfc9728":false,"pkceS256":false,"clientIdMetadataDocument":false,"dynamicClientRegistration":false}},"tls":{"observedAt":"2026-10-09T12:27:55.841Z","protocol":"TLSv1.3","chainValid":true,"chainError":null,"hostMatches":true,"subject":"zrev.ai","issuer":{"commonName":"WE1","organization":"Google Trust Services"},"validFrom":"2026-08-18T18:01:32.000Z","validTo":"2026-11-16T19:01:29.000Z","daysToExpiry":37,"sanCount":3,"fingerprint256":"F0:BA:38:8B:5F:59:CE:B2:18:62:E8:14:54:25:89:63:EE:64:E0:04:24:BC:D2:3C:B5:EF:F4:05:83:CA:D8:12"}}]},"verification":{"claimed":false,"claimedAt":null,"proofs":[]},"provenance":{"sources":[{"source":"mcp_registry","key":"ai.zrev/zrev","url":"https://registry.modelcontextprotocol.io/v0/servers/ai.zrev%2Fzrev","firstSeenAt":"2026-09-18T02:21:10.252Z","fetchedAt":"2026-10-09T00:19:26.247Z","normalizedAt":"2026-10-09T00:19:26.247Z"}]},"firstSeenAt":"2026-09-18T02:21:10.252Z","updatedAt":"2026-10-10T09:26:29.843Z"}