zRev AI

ai.zrevPublished by zrev.aiOfficial publisherv1.0.0Updated Oct 24, 2026

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

VerifiedStreamable HTTPWeb executableBusiness & Commerce

Overview

AI-generated overview

Lets an assistant look up zRev's services and results, estimate GTM ROI, grade an llms.txt, read a company homepage, and leave contact details.

What you can do
Returns zRev's company profile, typical benchmark results, the phases of a 60-day engagement and a 47-question GTM due diligence checklist across ten dimensions, all as read-only static text. estimate_roi projects annual impact from one company's numbers, grade_llms_txt scores a site's llms.txt with seven checks, and cold_read summarizes a company from its public homepage text only. book_call returns a scheduling link without booking, and leave_contact writes one lead record.
When to use it
Use when a user asks who zRev is, what it offers, how an engagement works or what results to expect, or wants to estimate GTM ROI from their own numbers, grade a site's llms.txt, get a quick read of a company homepage, or pull a GTM diligence checklist.
Requirements
Remote HTTP endpoint; no package to install. No authentication, environment variables or headers are declared. grade_llms_txt and cold_read need network access to fetch public pages from the given domain.
Before you install
leave_contact writes an email address, with optional name, company and note, as a lead record on zRev's side; use it only with the person's agreement. estimate_roi output is a model projection and the benchmark figures are described as typical, with a provenance caveat. grade_llms_txt and cold_read send requests to third-party sites.

Installation

In SourceWeft

  1. Open zRev AI in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.

Use with an agent

Paste this prompt into Claude Code, Codex, Cursor or another agent — or into SourceWeft chat. The agent reads this server's install guide, shows you its publisher, endpoint and sign-in, and adds it to your client once you agree. Keys never go into a command.

Read https://sourceweft.com/mcp/ai.zrev%2Fzrev/install.md and connect the MCP server it describes to my client. Before changing any config, show me its publisher, endpoint and sign-in method and wait for my OK. Never put an API key in a command or in a file I would commit; ask me where it should come from.

Read the install guide the agent follows

Other MCP clients

Add this to your client's mcpServers config.

{
  "mcpServers": {
    "zrev-ai": {
      "type": "http",
      "url": "https://go.zrev.ai/mcp"
    }
  }
}

Tools

9

about_zrev

About zRev

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.

Takes no parameters.

get_benchmarks

Typical engagement results

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.

Takes no parameters.

get_engagement_timeline

The 60-day engagement, phase by phase

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.

Takes no parameters.

estimate_roi

Estimate the ROI of AI across a GTM motion

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.

Parametersarrrequiredcacrequireddeal_sizerequiredteam_sizerequiredmonthly_leadsrequiredclose_rate_pctrequired

grade_llms_txt

Grade a site's llms.txt

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 fair-use limit per IP address with cold_read, and returns a plain-text notice when that limit is reached.

Parametersdomainrequired

cold_read

Cold-read a homepage

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 fair-use limit per IP address with grade_llms_txt, and returns a plain-text notice when that limit is reached.

Parametersdomainrequired

gtm_diligence_checklist

GTM due diligence checklist

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.

Parametersdimension

book_call

How to book an intro call

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.

Takes no parameters.

leave_contact

Ask zRev to get in touch

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.

Parametersnamenoteemailrequiredcompany

Version history

1
  1. v1.0.0LatestSep 17, 2026

Score

72% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 daysRequired25 pts
  • Auth declaredRequired10 pts
  • Tools listedRequired15 pts
  • DescriptionRequired15 pts
  • Logo10 pts

    Publish an icon in the registry entry.

  • Documentation15 pts

    Declare a GitHub repository with a README, or serve resource_documentation in the OAuth protected-resource metadata.

  • LicenseNot applicable

    A hosted service is used under its provider's terms, so no license is expected here. This check is left out of the percentage.