Mmcp.market

zRev AI MCP server

by zrev.ai·ai.zrev/zrev·v1.0.0

Grade any llms.txt, cold-read a homepage, run a B2B GTM ROI model, get a GTM diligence checklist.

C60/100grade C
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C60/100

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If you have run it, two minutes of your experience saves the next person an afternoon.

zRev AI tools (9, 1 write)

write = sends, deletes, buys or posts
  • about_zrevFree

    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, and contact details. Use this first when a user asks who zRev is, what it offers, or whether it suits their company. Read-only, static content, no arguments, no authentication, no rate limit.

  • book_callFree

    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 returns the scheduling link for the human to open themselves. Use when a user says they want to talk to zRev. If they would rather be contacted, use leave_contact instead. Read-only, static content, no arguments, no authentication, no rate limit.

  • cold_readFree

    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 that page and with no outside knowledge. Anything missing from the answer is missing from the homepage, which is the point: it shows what an AI assistant would tell a buyer about that company. Use when a user asks how their site, or a competitor's, reads to an AI. The summary is model-generated and can be wrong where the page is vague. Makes one outbound HTTP request to the public domain you pass; stores nothing about it. No authentication. Shares a limit of 12 calls per hour per IP address with grade_llms_txt, and returns a plain-text notice when that limit is reached.

  • estimate_roiwrite actionFree

    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 cost savings and the value of hours returned to the team, followed by the model's assumptions and a link to the interactive calculator preset to the same inputs. Use when a user wants a number for their own company; all six inputs are required, so ask for any that are missing rather than guessing. The output is an estimate from a fixed model, not a forecast or a quote. Pure calculation: nothing is stored, no external calls, no authentication, no rate limit.

  • get_benchmarksFree

    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 busywork automated, results that start inside 30 days and mature by 60. The response always ends with the provenance caveat: these are typical results benchmarked against comparable AI-powered GTM implementations and they vary by stack, data quality and adoption, so present them as typical, not guaranteed. Use when a user asks what results to expect. For an estimate on a specific company's numbers use estimate_roi instead. Read-only, static content, no arguments, no authentication, no rate limit.

  • get_engagement_timelineFree

    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 user asks how an engagement works, how long it takes, or what they would receive and when. Read-only, static content, no arguments, no authentication, no rate limit.

  • grade_llms_txtFree

    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 and the pass or miss result of each check as plain text. If the site has no llms.txt the response says so and links to zRev's free generator. Use when a user asks whether a site is readable by AI assistants or wants their llms.txt reviewed. Makes one outbound HTTP request to the public domain you pass; stores nothing about it. No authentication. Shares a limit of 12 calls per hour per IP address with cold_read, and returns a plain-text notice when that limit is reached.

  • gtm_diligence_checklistFree

    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 answers it and the red flag to watch for. Call with no arguments to get the list of ten dimensions; call with a dimension number from 1 to 10, or a keyword such as churn, pipeline or marketing, to get that dimension's questions in full. Use when a user is assessing a company's revenue engine before an investment or acquisition. Read-only reference content, no authentication, no rate limit.

  • leave_contactFree

    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 tool here that writes data: it creates one lead record on zRev's side and triggers no email to the address given. Use only when the human you are assisting has explicitly asked to be contacted by zRev; never call it speculatively or with an address the user has not given you for this purpose. Submitting the same email again updates the existing record rather than creating a duplicate. No authentication. Rate-limited per IP address.

Public scan report

scanner v0.1.5 · 2026-09-19 · same rubric, same numbers if you re-run it

1 high1 low
  • Code scanremote-only server, no package to scann/a
  • Live reliabilityremote reachable in 401ms20/20
  • Tool poisoning9 tool descriptions checked15/15
  • Auth qualityopen endpoint exposes 1 write-action tools with no auth3/15
  • Maintenanceno repository listed3/15
  • Maintainer identityverified namespace with website, no repo4/10

Findings (2)

  • highWrite-action tools reachable without authenticationauth.open-write
  • lowNo source repository listedmaint.no-repo
Overall 60/100. Components that don't apply are left out of the denominator. Any critical finding is an F.RubricAppeal a findingJSON

Install directly

claude mcp add --transport http zrev https://go.zrev.ai/mcp
Add to Cursor

zRev AI: common questions

Is zRev AI MCP server safe?
With care: it is graded C, so read the findings first (60/100). Read the zRev AI safety report
How do I install zRev AI?
It runs remotely at go.zrev.ai. Add it to Claude Code, Claude Desktop or Cursor with the snippets above, or call it through the mcp.market gateway without installing anything.
Does zRev AI need an API key?
Not as far as the registry entry and our scan can tell: no credentials are declared or required.
Is zRev AI maintained?
The latest release is v1.0.0.
Is zRev AI up?
100% of our last 6 checks got an answer. We check remote servers about four times a day.
What can I use instead of zRev AI?
Servers from other publishers that do the same job: Testrail MCP server.

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