AI workflow MCP-native Claude · ChatGPT · Gemini · MCP

The Pipeline Engine

Describe the kind of client you want in your own words, and get back a list of matching companies, each with the right decision-maker, a verified email, and a tailored opening line.

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What it does

  1. Runs on Claude, ChatGPT, or Gemini.
  2. Pulls candidate companies by your ICP, in any region you specify.
  3. Finds the right decision-maker at each company.

The Breakdown

The build steps, prompt architecture, and a worked walkthrough. Open to members.

01 The architecture: three services, one dry-run gate

02 Turning your words into an ICP filter

03 Discovery, the decision-maker, and one fresh signal

04 Email verification and the spend gate

05 The one-line opener, and why you write the rest

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How to install

Every workflow runs on the AI you already use. Pick your platform; each setup takes a couple of minutes.

01 Claude Code Local install · recommended

Drop the unzipped folder into your Claude Code skills directory and restart.

  1. Unzip the pipeline-engine bundle from your purchase email.
  2. Copy the whole pipeline-engine/ folder into ~/.claude/skills/.
  3. Add the Apify MCP snippet below to ~/.claude/mcp.json. Restart Claude Code.
  4. In any project, say "run the Pipeline Engine".
{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com",
      "headers": { "Authorization": "Bearer YOUR_APIFY_TOKEN" }
    }
  }
}
02 Claude Desktop MCP-native

Paste SKILL.md into a Project and connect the Apify MCP. The skill is live in every chat in that Project.

  1. Open Claude Desktop → Settings → Developer → Edit Config. Add the snippet below under mcpServers.
  2. Restart Claude Desktop.
  3. Create a Project named "Pipeline Engine". Paste SKILL.md from the bundle into Project Instructions.
  4. Open a chat in the Project and say "run the Pipeline Engine".
{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com",
      "headers": { "Authorization": "Bearer YOUR_APIFY_TOKEN" }
    }
  }
}
03 ChatGPT Project or Custom GPT

Build a Project or Custom GPT that wraps SKILL.md. Requires a plan with MCP connectors.

  1. Open ChatGPT → Settings → Connectors → Add MCP server. Paste the Apify MCP URL.
  2. Create a new Project (or Custom GPT). Paste SKILL.md into Instructions.
  3. Open a chat with the Project or GPT and say "run the Pipeline Engine".
04 Cursor MCP-native

Drop the bundle into a folder Cursor reads and reference SKILL.md from your chat.

  1. Copy the pipeline-engine/ folder into ~/.cursor/skills/ (or any folder Cursor watches).
  2. Open Cursor Settings → MCP → Add Server. Paste the Apify MCP URL.
  3. In a chat, reference @pipeline-engine/SKILL.md and say "run the Pipeline Engine".

Read the full install guide

Stacks with

These AI workflows are designed to chain together. Run one's output through another and you get a real production pipeline.

  • AI Proposal Drafter

    Pairs with AI Proposal Drafter from MWM Issue 03. When a Pipeline Engine lead books a discovery call, hand the transcript to AI Proposal Drafter and the SOW comes back in your studio's voice.

  • AI Editor In Chief

    Pairs with AI Editor In Chief from MWM Issue 02. The Pipeline Engine writes the opener. AI Editor In Chief writes the rest of the email through your voice fingerprint.

Also referenced in

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