How to Optimise Your Blog with Claude Code and Peec AI MCP
Last updated: 28 May 2026
Short answer: use Peec AI MCP to find where AI engines mention competitors, retrieve sources, and miss your pages. Then use Claude Code to patch the article: answer-first intro, prompt-shaped headings, source-led sections, FAQPage schema, Article schema, internal links, and mobile-safe visuals.
This workflow pairs well with the AI Heroes AI Search Blog Optimiser for Claude Code. That tool focuses on article anatomy. Peec AI MCP adds live visibility and source evidence.
The blog optimisation loop
- Pick a target prompt class, not just a keyword.
- Use Peec to check visibility, position, sentiment, share of voice, and source URLs for that prompt class.
- Identify competitor pages and third-party sources that AI engines retrieve or cite.
- Ask Claude Code to compare your article with the answer shape shown in those sources.
- Patch the article so it answers faster, defines entities cleanly, includes comparison context, and exposes FAQs.
- Add or verify Article, FAQPage, HowTo, Breadcrumb, and sitemap coverage where appropriate.
- Run a browser pass on desktop and mobile.
- Monitor the same prompt set again after the page is crawled and re-read.
What to change in the article
| Gap from Peec | Blog update |
|---|---|
| AI cites competitor definition pages | Add a concise definition and comparison block near the top |
| AI retrieves forums or UGC | Add real-world objection handling and community-source context |
| AI cites listicles | Add transparent selection criteria and alternatives |
| Own page retrieved but not cited | Improve extractable answer blocks, schema, and source clarity |
| Sentiment is weak | Add proof, caveats, use-case fit, and customer-safe positioning |
Claude Code prompt
Use Peec AI MCP evidence to improve this blog post for AI-search visibility.
Do not invent Peec data. Resolve names before reporting. Keep recommendations
tied to prompts, engines, source URLs, or Peec Actions. Patch only the article,
schema, internal links, and tests needed for this page. Run desktop and mobile
browser QA after the build.
Where the AI Search Blog Optimiser fits
Use the optimiser as the article-level checklist: title, answer-first intro, prompt-shaped headings, extractable tables, FAQs, schema, internal links, and CTA. Use Peec as the evidence layer: which prompts, engines, sources, and competitors justify the changes.
For Schmitdy, this becomes the recurring growth loop after an AI Search audit: Peec finds the gap, Claude Code patches the page, the harness checks the page, and the next Peec cycle measures whether AI engines start retrieving or citing it.
Source and fact ledger
- Peec AI MCP introduction:
https://docs.peec.ai/mcp/introduction - Peec AI source and URL tools:
https://docs.peec.ai/mcp/tools - AI Heroes AI Search Blog Optimiser:
https://www.ai-heroes.co/en-gb/free-tools/ai-search-blog-optimiser/claude-code
Frequently Asked Questions
Founder, Schmitdy
Marco builds AI search growth systems that turn prompts, sources, content, and agents into pipeline for B2B teams.
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See where AI search is already choosing your competitors
Request the free AI Search audit and get the prompts, source gaps, and next actions that matter for pipeline.
