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# DataForSEO Integration Guide
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## Overview
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DataForSEO provides real keyword data, competitor intelligence, and AI search optimization metrics. This replaces guesswork with data-driven decisions.
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**MCP Access:** DataForSEO tools are available through MCP. Use them directly in your research workflow.
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## Budget Protocol
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- **Per session limit:** $0.50 (unless user explicitly approves more)
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- **Monthly budget:** ~$10
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- **Always report:** Show user what API calls you're making and estimated cost
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## Core Principle
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Start with seeds → expand with related → filter by opportunity → verify with SERP.
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Don't chase high-volume competitive keywords. Find gaps where we can win.
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---
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## For @spy: Competitive Intelligence
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### Competitor Keywords
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```
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Tool: dataforseo_labs_google_ranked_keywords
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Use: See what keywords competitors rank for
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Target: fal.ai, replicate.com, runware.ai, cloudinary.com
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```
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### Backlink Analysis
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```
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Tool: backlinks_summary, backlinks_referring_domains
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Use: Where competitors get links, potential outreach targets
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```
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### Domain Intersection
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```
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Tool: dataforseo_labs_google_domain_intersection
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Use: Find keywords multiple competitors rank for (validated demand)
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```
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### LLM Mentions (GEO)
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```
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Tool: ai_optimization_llm_mentions_search
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Use: Check if Banatie or competitors mentioned in AI responses
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Platform: chat_gpt, google (AI Overview)
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```
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---
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## For @strategist: Keyword Research
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### Search Volume
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```
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Tool: keywords_data_google_ads_search_volume
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Use: Get real monthly search volume for keyword list
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Input: Up to 1000 keywords per request
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```
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### Keyword Difficulty
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```
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Tool: dataforseo_labs_bulk_keyword_difficulty
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Use: Score 0-100, lower = easier to rank
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Filter: KD < 50 for realistic targets
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```
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### Related Keywords
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```
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Tool: dataforseo_labs_google_related_keywords
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Use: Expand seed keywords, find long-tail opportunities
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Depth: 1-4 (start with 1, go deeper if needed)
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```
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### Search Intent
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```
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Tool: dataforseo_labs_search_intent
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Use: Classify keywords as informational/navigational/commercial/transactional
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Match: Content type should match intent
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```
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### AI Search Volume (GEO Priority)
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```
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Tool: ai_optimization_keyword_data_search_volume
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Use: Keywords popular in AI search (ChatGPT, Perplexity)
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Why: Early indicator of emerging queries
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```
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### Research Workflow
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1. **Start with seeds** (3-5 per topic)
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2. **Get search volume** for seeds
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3. **Expand** top 3 by volume with related keywords
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4. **Filter:** Volume > 50, KD < 50
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5. **Check intent** for finalists
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6. **SERP analysis** for top candidates
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---
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## For @seo: Optimization & Verification
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### SERP Analysis
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```
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Tool: serp_organic_live_advanced
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Use: See current top 10 results, SERP features present
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Check: Featured snippets, PAA, video results
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```
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### On-Page Analysis
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```
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Tool: on_page_instant_pages
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Use: Technical SEO check of specific URL
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After: Publishing, verify optimization
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```
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### LLM Responses (GEO)
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```
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Tool: ai_optimization_llm_response
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Use: See how AI models answer our target queries
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Why: Optimize content for AI citations
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```
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---
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## Key Learnings
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**Problem-aware keywords often have zero volume.**
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People search for solutions, not problems. "placeholder images slow" = 0 volume. "generate images api" = real volume.
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**Related keywords > seed keywords.**
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Your initial guesses are rarely the best targets. Let data guide expansion.
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**Brand keywords are useless.**
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"cloudinary pricing" means they already chose Cloudinary. Target problem/solution queries.
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**Low KD + decent volume = opportunity.**
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Don't chase "ai image generation" (KD 80+). Find "generate images for nextjs" (KD 30, volume 200).
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---
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## Output Format
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When reporting keyword research:
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```markdown
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## Keyword Research: [Topic]
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### Seeds Analyzed
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| Keyword | Volume | KD | Intent |
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|---------|--------|----|----|
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| ... | ... | ... | ... |
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### Top Opportunities
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| Keyword | Volume | KD | Rationale |
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|---------|--------|----|----|
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| ... | ... | ... | Why this is a good target |
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### Recommendations
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[What content to create based on this data]
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### API Calls Made
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[List of tools used, estimated cost]
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```
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