Outbound Engine Mcp

io.github.closermethod由 GitHub 帳號 closermethod 發布v1.0.2更新於 Oct 24, 2026

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

已驗證STDIO僅桌面效率與工作流商業與電商

概覽

AI 產生的概覽

一套冷開發外聯方法層，讓助理用工具建立、審查與追蹤冷開發提案，適用於品牌合作、UGC、求職、播客與客戶專案。

可以做什麼
  • 把冷開發提案拆成 HOOK/BRIDGE/SOFT ASK 結構，並依目標類型給出四個替換變數
  • 審查草稿中的違規點，例如冷訊息中報價、空泛開場、直接提出大要求，並提供改寫方案
  • 產生五步追蹤階梯，並針對價格詢問、已讀不回、曝光交換等回覆類型給出下一步動作
  • 產生三選項報價菜單，並掃描回覆或需求簡報中的警訊，如免費試做、按成效付費
  • 把整套方法打包成單一內容，可直接放入系統提示
適用情境
適合助理起草或審閱冷開發外聯時使用，讓內容依循以取得回覆為目標的一致結構，而非冗長空泛的推銷。也適合創作者與自由工作者向品牌合作、贊助、職缺、播客或客戶專案提案，需要審查與追蹤計畫時使用。
執行需求
以 stdio 本機程序方式執行，透過 npm 套件 outbound-engine-mcp 安裝，需要 Node.js 執行環境。未宣告需要帳號、API 金鑰或環境變數。
安裝前請注意
它不傳送訊息也不擷取潛在客戶，只回傳框架與審查結果，傳送與研究仍須自行處理。輸出屬方法建議，不構成法律意見，README 提醒遵守所在管道與地區的平台規則及外聯法規。README 另提到有付費產品。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Outbound Engine Mcp，將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only，透過 STDIO。 STDIO 服務會啟動本機處理程序，因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

README

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

typescript
// 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

來源：README.md，提交 d16a11f

工具

0
SourceWeft 尚未在沙箱中啟動過該軟體包，因此其工具未知。

版本歷史

1
  1. v1.0.2最新Sep 16, 2026

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