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egebese/dataseo-mcp · Archived

dataseo-seo-research

Use DataSEO MCP for SEO research workflows including backlink analysis, keyword research, traffic checks, domain comparison, backlink opportunity discovery, AI search query planning, and SEO content briefs.

First seen Jul 6, 2026

Installation

$ npx skills add egebese/dataseo-mcp --skill dataseo-seo-research
View on skills.sh ↗ GitHub repository ↗

Summary

  • Use DataSEO MCP for SEO research workflows including backlink analysis, keyword research, traffic checks, domain comparison, backlink opportunity discovery, AI search query planning, and SEO content briefs.
  • Use this whenever the user asks to investigate a domain, compare competitors, plan SEO content, find backlink gaps, or generate search-intent queries with DataSEO MCP.

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

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Gemini CLI Not declared
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OpenCode Not declared

Repository health

Stars 187
License LICENSE
Default branch main
Open issues 1
Status Archived

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 3,356 B
  • docs SUMMARY.md 402 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 2 installs

SKILL.md

DataSEO SEO Research

Use this skill when a user wants SEO research through DataSEO MCP tools. The workflow should produce concise, decision-ready findings, not raw dumps.

Required Setup

Before calling Ahrefs-backed tools, ensure at least one CAPTCHA provider is configured:

  • CAPSOLVERAPIKEY
  • ANTICAPTCHAAPIKEY

AI query planning and content briefs improve when OPENROUTERAPIKEY is set. If it is missing, continue with non-AI SEO data and clearly mark AI output as unavailable.

Tool Selection

Choose the narrowest tool that answers the request:

User intent Tool
Backlink profile for one domain getbacklinkslist
Keyword ideas from seed terms keyword_generator
Traffic estimate for a domain or URL get_traffic
Ranking difficulty / SERP snapshot keyword_difficulty
AI search query ideas by intent aisearchqueries
Quick domain health summary domain_overview
Competitor comparison compare_domains
Link-building source gaps backlink_opportunities
Article or landing-page brief seocontentbrief

Research Workflow

  1. Normalize all domains to bare domains unless the user asks for an exact URL.
  2. For one-domain audits, start with domain_overview, then deepen with

getbacklinkslist or keyword_generator only if needed.

  1. For competitor work, use compare_domains first, then

backlink_opportunities for link-building next steps.

  1. For content planning, use keyworddifficulty and keywordgenerator; add

aisearchqueries or seocontentbrief when AI is configured.

  1. Summarize findings by priority: opportunity, evidence, recommended action.

Output Format

Use this structure unless the user asks for something else:

## Summary
- One-sentence SEO readout.

## Findings
- Domain/keyword evidence with metrics.

## Opportunities
- Prioritized actions and why they matter.

## Next Steps
- 3-5 concrete tasks.

Safety and Quality

  • Do not claim live accuracy beyond the returned tool data.
  • Do not scrape or bypass sites outside the MCP provider behavior.
  • Do not expose API keys, CAPTCHA tokens, signed inputs, or raw provider

responses.

  • Prefer comparisons and patterns over long raw tables.
  • Mention when a domain or keyword appears missing from upstream data.

Examples

Input: "Analyze backlinks for suparank.io"

Action: Call getbacklinkslist(domain="suparank.io"), then summarize domain rating, referring domains, strongest sources, anchors, and link-building angles.

Input: "Compare suparank.io with its competitors"

Action: Call compare_domains(domains=["suparank.io", ...]), then report traffic/backlink differences and practical positioning notes.

Input: "Create a brief for AI SEO audit"

Action: Call seocontentbrief(keyword="AI SEO audit"); if AI is unavailable, fall back to keyworddifficulty and keywordgenerator.