MCP server

zRev AI Official

ai.zrev/zrev

Checked 26 Oct 2026, 08:29 UTC · Connected to it and listed its tools

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

Website

At a glance

Type

MCP server

Publisher

zrev.ai (verified by the MCP Registry)

Status

Working at last check

Tools

9

Token cost

About 2,033 tokens per request

Sets up in

Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok

Last checked

26 Oct 2026, 08:29 UTC

Connect it to your agent

Add to CursorAdd to VS CodeVS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

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

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.zrev]
url = "https://go.zrev.ai/mcp"

Gemini CLI

{"mcpServers":{"zrev":{"httpUrl":"https://go.zrev.ai/mcp"}}}

Cursor

{"mcpServers":{"zrev":{"url":"https://go.zrev.ai/mcp"}}}

VS Code

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

Antigravity

agy mcp add zrev https://go.zrev.ai/mcp

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"zrev","server_url":"https://go.zrev.ai/mcp","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"zrev","server_url":"https://go.zrev.ai/mcp"}

Tools

• about_zrev ~126 tokens
  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 cont
• book_call ~140 tokens
  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
• cold_read ~268 tokens
  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
• estimate_roi ~388 tokens
  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 t
• get_benchmarks ~215 tokens
  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 typica
• get_engagement_timeline ~122 tokens
  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 authe
• grade_llms_txt ~240 tokens
  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
• gtm_diligence_checklist ~236 tokens
  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
• leave_contact ~298 tokens
  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

Browse

• Email
• Booking and scheduling

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