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Outbound Engine MCP

by closermethodversion 1.0.2i★ –iRuns on your computer
Registry nameio.github.closermethod/outbound-engine-mcp

Install

Overview

Description from the maker (original English)

One cold-outreach engine for any target: HOOK/BRIDGE/SOFT-ASK, follow-up ladder, reply playbook.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Other

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • The registry lists no key to fill in.

You need

  • npmNode.js installed (for the npx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "outbound-engine": {
      "command": "npx",
      "args": [
        "-y",
        "outbound-engine-mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add outbound-engine -- npx -y outbound-engine-mcp

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "outbound-engine": {
      "command": "npx",
      "args": [
        "-y",
        "outbound-engine-mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "outbound-engine": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "outbound-engine-mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account closermethod, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

  • More stars than 0% of the other 32424 servers in this category
  • Published to the registry more recently than 17% of the other 32424 servers in this category
  • Basic checks equal to or better than 100% of the other 32424 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Outbound Engine MCP safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (1.0.2) reached the registry 4 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, BankBridge

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Spec Driven Development

by formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

Runs on your computer★ 440MITUpdated 14 months ago
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Remote Desktop Commander

by desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

Runs in the cloud★ 211Updated yesterday
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BankBridge

by bankbridge-money

Works in any MCP agent, including local models. Read-only bank accounts, spending, investments.

Runs in the cloudUpdated today
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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

Outbound Engine MCP

The cold-outreach method layer for AI agents. One engine, any target: brand deals, UGC, newsletter sponsorships, jobs, podcasts.

Built from the method behind The Outbound Engine.

Disclaimer. Outputs are structured outreach-method frameworks based on documented practice. Results vary by niche, proof quality, and consistency. Not legal advice. Follow platform rules and outreach law for your channel and region.


Why This Exists

Every AI agent that drafts cold outreach today has the same failure mode: it writes long, polite, generic pitches that ask a stranger for the biggest possible thing on the first touch. Those messages don't get replies, and outreach that doesn't get replies doesn't get deals.

This MCP encodes one rule and enforces it with tools:

A cold pitch is not trying to close a deal. It is trying to get a reply. The deal closes in the follow-up.

It does NOT send messages and does NOT scrape prospects. It is the method layer: give it a draft, a target type, or a reply — get back structure, violations, and the next move.

7 Tools

ToolWhat it returns
structure_cold_pitchHOOK / BRIDGE / SOFT ASK structure + the 4 swap variables (who to pitch, signal to research, proof to lead with, soft-ask object) per target type
audit_cold_messagePASS/FAIL audit of a draft: money in a cold message, identity-first opener, generic hook, hard ask, length over ~90 words, multiple asks — with a rewrite recipe
build_followup_ladderThe 5-step ladder (Day 3 / 7 / 12 / 18 / 25) — where 80% of deals actually close. The Day 25 break-up alone pulls ~30% of replies
handle_replyThe next move for any reply type: price question, interested, not now, no budget, exposure offer, spec request, pay-on-performance, ghosted
build_pricing_menuThe 3-option menu (Starter / Most Popular / Full) + the two scoping questions to ask first. Drop scope, never price
detect_red_flagsScans a reply or brief for walk-away signals: exposure-pay, spec work, pay-on-performance, budget mismatch, scope creep
get_full_packThe complete engine as one payload — drop it into a Claude Project system prompt

Sample Use

// Agent drafted a cold DM for a brand deal. Before sending:

mcp.call("audit_cold_message", { message: "Hi, I'm a UGC creator with 50k followers! I love your brand. My rate is $500/video...", target_type: "brand_deal" }); // Returns: FAIL — no_money_in_cold_message, no_identity_first_opener, // specific_hook_required + a 3-move rewrite recipe.

// Prospect replied asking "what do you charge?" mcp.call("handle_reply", { reply_type: "price_question" }); // Returns: don't send one number — two scoping questions first, then the 3-option menu.

Target Types

brand_deal · ugc · newsletter_sponsorship · job · podcast · client_work

Same engine, four swapped variables per target. That's the whole trick.

The Full System

This MCP is the free method layer. The full Outbound Engine product adds per-target research packs, an onboarding intake that builds your proof inventory, and the daily operating system — at elisabethhitz.com.

Built By

Elisabeth Hitz — 10+ years of B2B enterprise sales experience across ad-tech, SaaS, media, and global hiring. Now building MCP servers for the AI agent ecosystem.

License: MIT

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