Connect zRev AI and your agent gets 9 tools, among them about_zrev, book_call, cold_read. It answers at https://go.zrev.ai/mcp over streamable HTTP, and it listed its tools to an anonymous client, so no sign-in was needed for that. Our probes reached it 4 of 4 times since 17 September 2026; the last check, on 25 October 2026, succeeded.
Grade any llms.txt, cold-read a homepage, run a B2B GTM ROI model, get a GTM diligence checklist.
Description as the publisher wrote it.
| Tool | What it does |
|---|---|
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 offer |
book_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 |
cold_read | 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 mis Inputs: domain |
estimate_roi | 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 a Inputs: arr, deal_size, monthly_leads, close_rate_pct, cac, team_size |
get_benchmarks | 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 respo |
get_engagement_timeline | 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 |
grade_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 Inputs: domain |
gtm_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 t Inputs: dimension |
leave_contact | 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 Inputs: email, name, company, note |
Every block below points at https://go.zrev.ai/mcp. Pick your client and copy.
claude mcp add --transport http zrev-ai https://go.zrev.ai/mcp
{
"mcpServers": {
"zrev-ai": {
"command": "npx",
"args": ["-y", "mcp-remote", "https://go.zrev.ai/mcp"]
}
}
}{
"mcpServers": {
"zrev-ai": {
"url": "https://go.zrev.ai/mcp"
}
}
}{
"servers": {
"zrev-ai": {
"type": "http",
"url": "https://go.zrev.ai/mcp"
}
}
}{
"context_servers": {
"zrev-ai": {
"url": "https://go.zrev.ai/mcp"
}
}
}{
"mcpServers": {
"zrev-ai": {
"serverUrl": "https://go.zrev.ai/mcp"
}
}
}{
"mcpServers": {
"zrev-ai": {
"url": "https://go.zrev.ai/mcp"
}
}
}name: zRev AI
version: 0.0.1
schema: v1
mcpServers:
- name: zRev AI
type: streamable-http
url: https://go.zrev.ai/mcp{
"mcpServers": {
"zrev-ai": {
"httpUrl": "https://go.zrev.ai/mcp"
}
}
}{
"mcpServers": {
"zrev-ai": {
"type": "http",
"url": "https://go.zrev.ai/mcp"
}
}
}{
"mcpServers": {
"zrev-ai": {
"url": "https://go.zrev.ai/mcp"
}
}
}goose://extension?url=https%3A%2F%2Fgo.zrev.ai%2Fmcp&type=streamable_http&id=zrev-ai&name=zRev%20AI
It answered our last check on 25 October 2026 in 161 ms. Over 4 checks since 17 September 2026 it answered 4. Status here comes from Neuronto's own probes, not from the publisher.
Yes. It is published by zrev.ai and served from go.zrev.ai, the vendor's own domain: https://go.zrev.ai/mcp.
9, as returned by the server's own tools/list on 24 September 2026: about_zrev, book_call, cold_read, estimate_roi, get_benchmarks, get_engagement_timeline, grade_llms_txt, gtm_diligence_checklist, and 1 more.
It answered our last check on 25 October 2026 in 161 ms. Over 4 checks since 17 September 2026 it answered 4.
Put the server under mcpServers in ~/.cursor/mcp.json with the URL https://go.zrev.ai/mcp. The exact JSON is above, with the same setup for Claude Code, Claude Desktop, VS Code, Windsurf, Zed, Gemini CLI and the rest.
It listed its tools to an anonymous client, so reading the tool list needs no key. Individual tools can still ask for credentials in their own inputs.
Publisher: ai.zrev. Endpoint host: go.zrev.ai. ARD identifier: urn:air:ai.zrev:mcp:zrev.
First indexed 17 September 2026. The tools are exactly what the server returned; nothing on this page
is inferred from its name. Ranking in Neuronto search is never for sale.