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Using SEO MCP, compare AI search visibility for website builders across all major LLM engines (ChatGPT, Perplexity, Gemini, AI Overview, and AI Mode) in the US market.

Target: [wix.com] (brand: ["Wix"])
Competitors:
- [weebly.com] (brand: ["Weebly"])
- [hostinger.com] (brand: ["Hostinger"])
- [squarespace.com] (brand: ["Squarespace"])
- [webflow.com] (brand: ["Webflow"])

Use base_domain scope. First, get the leaderboard. Create a heatmap here. Then, for each domain (target and all competitors), pull 20 ChatGPT prompts: 10 where the domain appears as a source (link mention) and 10 where the brand is mentioned by name. Show query text and sources to validate results.

Analyze the topics across all prompts. Summarize: Who dominates AI search in the website builder space? What topic clusters does each brand own?
Where does each have strong presence, and where are the gaps?

Using SE Ranking MCP, pull the latest website audit results for [seranking.com]:
1. Pull the latest audit results — top critical issues
2. Compare with last month's audit snapshot
3. Identify NEW issues that appeared since last check
4. For each new issue, explain the SEO impact and suggest a fix
5. Prioritize by traffic-at-risk

Save as a client-ready audit change report.

You are a senior SEO content strategist. [Notion] ([notion.com]) wants to publish
a new blog post to capture organic traffic they're currently losing to
competitors. Your job: find the best topic opportunity and deliver a complete
content editor brief a writer can start from tomorrow.

Using SE Ranking MCP:

1. Pull [Notion]'s domain overview and top organic keywords in the US market.
   Save to `[notion-content-brief]/01-domain-overview.md`

2. Identify [Notion]'s top 5 organic competitors.
   Save to `[notion-content-brief]/02-competitors.md`

3. Run a keyword gap analysis — find high-value keywords competitors rank for
   that [Notion] doesn't. Focus on informational intent, volume >1,000/mo,
   keyword difficulty <40.
   Save to `[notion-content-brief]/03-keyword-gaps.md`

4. From the gaps, pick the single best topic cluster for a blog post. Explain
   your reasoning (traffic potential, difficulty, relevance to [Notion]'s
   product).

5. For that chosen topic:
   a. Pull who currently ranks and what type of content wins
   b. Get related keywords and long-tail variations
   c. Get question-based keywords people are asking
   d. Check AI Search — are LLMs mentioning any brands for this topic?
   Save all raw data to `[notion-content-brief]/04-ranking-and-keywords.md`

6. Analyze the top 3 ranking articles: what subtopics do they all cover?
   What do they miss? Where can [Notion]'s post be better?
   Save to `[notion-content-brief]/05-content-analysis.md`

7. Find 5 existing [Notion] pages/posts that rank well and could serve as
   internal linking sources for this new post.
   Save to `[notion-content-brief]/06-internal-links.md`

8. Deliver a final Content Editor Brief in `[notion-content-brief]/BRIEF.md`:
   - Recommended title (3 options)
   - Target keyword + secondary keywords with volumes
   - Suggested H2/H3 structure with what to cover in each section
   - Content gaps the current top results miss ([Notion]'s angle)
   - Internal linking plan (which existing pages, with anchor text)
   - AI Search insight — how to get mentioned by LLMs
   - Estimated word count and traffic potential
   - Format it so a freelance writer can start immediately