Claude Code Skills for Marketing Teams

Claude Code skills are reusable prompt-plus-tool bundles that give Claude Code domain-specific capabilities. For marketing teams, this means adding SERP research, competitor monitoring, content brief generation, and keyword analysis to your terminal without building custom tooling. Connect a SERP API via MCP, and Claude Code becomes a research assistant that works with live data.

Skills vs Prompts

A prompt tells Claude what to do. A skill gives Claude the tools to do it. Telling Claude "analyze competitor rankings" without a SERP tool means it guesses from training data. A skill that connects Claude Code to a SERP API means it pulls actual rankings, extracts SERP features, and reports what is happening today. The difference is between creative writing and data analysis.

Setting Up SERP Research in Claude Code

// .mcp.json in your project root
{
  "mcpServers": {
    "scavio": {
      "url": "https://mcp.scavio.dev/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_KEY"
      }
    }
  }
}

Marketing Workflows That Work

• Content gap analysis: pull SERPs for 20 target keywords, identify topics where competitors rank but you do not
• PAA mining: extract People Also Ask questions across a keyword cluster to build FAQ sections and content outlines
• AI Overview monitoring: track which of your pages get cited in AI Overviews and which competitor pages are cited instead
• Product research: pull Amazon results to understand how competitors position and price similar products
• Social listening: search Reddit and TikTok for brand mentions and competitor discussions

Example: Keyword Cluster Research

import requests, os

API_KEY = os.environ["SCAVIO_API_KEY"]
BASE_URL = "https://api.scavio.dev/api/v1/search"
HEADERS = {"x-api-key": API_KEY, "Content-Type": "application/json"}

keywords = [
    "email marketing automation",
    "best email marketing tools 2026",
    "email marketing vs marketing automation",
    "email marketing ROI benchmarks",
]

for kw in keywords:
    resp = requests.post(BASE_URL, headers=HEADERS,
        json={"query": kw, "country_code": "us"})
    data = resp.json()
    organics = data.get("organic_results", [])
    paa = data.get("people_also_ask", [])
    print(f"\n--- {kw} ---")
    print(f"  Top 3: {[r['title'][:50] for r in organics[:3]]}")
    print(f"  PAA: {[q['question'] for q in paa[:3]]}")

Cross-Platform Research

Marketing does not happen on Google alone. Scavio covers Google, Amazon, YouTube, Reddit, TikTok, and Walmart from one API key. A single research session can pull Google rankings for your target keyword, YouTube videos ranking for the same topic, Reddit discussions about the category, and TikTok content trends. This cross-platform view is what separates a content strategy from a keyword list.

Why Terminal Over Browser

Browser-based SEO tools require switching between your editor and browser tabs. Terminal-based research via Claude Code keeps you in one environment. You describe what you need in natural language, Claude researches it using live APIs, and the results land directly in your conversation. For teams that create content in markdown or code-based CMS platforms, this removes the context-switch overhead that fragments research and writing into separate workflows.