ai-acquisition-search

v0.5.0

Evidence-based customer acquisition decision engine for Claude Code: research, campaign testing, performance analysis, and next-action decisions.

Claude Code2 Skills1 MCP serverstdio

By AI Acquisition SearchLicense: MIT0 GitHub starsUpdated 2 weeks ago

Directory evidence

Runtimes: Claude Code
Parsed components: 3 skill or MCP entries
Source updated: Oct 4, 2026
Manifest status: Canonical path parsed

The directory validates manifest shape and source location. It does not execute the plugin or provide a security endorsement. Review the indexing methodology →

Install ai-acquisition-search for Claude Code

Installs for the current user

claude plugin marketplace add IchenDEV/agent-plugin-mkt
claude plugin marketplace update agent-plugin-marketplace
claude plugin install ai-acquisition-search-2@agent-plugin-marketplace

Paste and run these commands in a terminal with Claude Code. They add and refresh the PluginsMP catalog, then install this plugin.

The installer fetches third-party code from the source repository shown on this page. This directory validates manifest structure and source location, but does not perform a security audit; review the manifest, components, and source before installing.

Get the source manually

$ git clone https://github.com/shunai394-hash/ai-acquisition-search

Clone the source repository, then follow its setup instructions to add the plugin to a compatible client. The repository root is the plugin root.

Plugin files

ai-acquisition-search/

├── .claude-plugin/plugin.json
├── skills/acquisition-cycle/SKILL.md
├── skills/ai-brand-operator/SKILL.md
└── .mcp.json

Included Skills2

acquisition-cycleskills/acquisition-cycle/SKILL.md

Analyze a product URL, decide the next revenue-oriented acquisition test, create an ad video with Higgsfield, and collect performance data. Use when the user asks what to publish next, wants an ad cycle, or wants to turn a product into a measurable acquisition experiment.

ai-brand-operatorskills/ai-brand-operator/SKILL.md

Use this skill when operating the AI acquisition workflow from product research through evidence-based campaign decisions, production briefs, publishing, and performance learning.

MCP servers1

ai-acquisition-searchstdio

command: npx
args: tsx ${CLAUDE_PLUGIN_ROOT}/src/mcp/server.ts
env.HF_API_KEY_ID: ${HF_API_KEY_ID}
env.HF_API_KEY_SECRET: ${HF_API_KEY_SECRET}
env.GEMINI_API_KEY: ${GEMINI_API_KEY}

MCP configuration uses runtime-provided plugin path placeholders such as ${PLUGIN_ROOT} or ${CLAUDE_PLUGIN_ROOT}. Review the manifest for the runtime-specific expansion rules.

Plugin manifests1

.claude-plugin/plugin.json

{
  "name": "ai-acquisition-search",
  "description": "Evidence-based customer acquisition decision engine for Claude Code: research, campaign testing, performance analysis, and next-action decisions.",
  "version": "0.5.0",
  "author": {
    "name": "AI Acquisition Search"
  },
  "repository": "https://github.com/shunai394-hash/ai-acquisition-search",
  "homepage": "https://github.com/shunai394-hash/ai-acquisition-search",
  "license": "MIT",
  "keywords": [
    "customer-acquisition",
    "marketing",
    "advertising",
    "decision-engine",
    "analytics",
    "mcp"
  ]
}