Ahrefs MCP

Access Ahrefs SEO data for site analysis, keyword research, backlink and competitor insights, rank tracking, and technical SEO audits via MCP integration.

MIT-0 · Free to use, modify, and redistribute. No attribution required.
0 · 541 · 1 current installs · 1 all-time installs
MIT-0
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Purpose & Capability
Name and description match the SKILL.md and reference files: the skill is explicitly about querying Ahrefs via the Model Context Protocol (MCP). Required resources (none declared) and the runtime instructions only reference Ahrefs endpoints and Ahrefs account setup, which is proportionate to the stated purpose.
Instruction Scope
SKILL.md and references focus on formulating Ahrefs queries, setup, and workflows. They do not instruct reading unrelated files, accessing unrelated environment variables, or exfiltrating data to third-party endpoints. The only external endpoints are Ahrefs domains and an optional GitHub repo for enterprise local-server setup.
Install Mechanism
Instruction-only skill with no install spec and no code shipped. The only install-like guidance is an optional git clone of an Ahrefs GitHub repo for enterprise local MCP, which is sensible and points to a standard GitHub location. No downloads from unknown hosts or extractable archives are present.
Credentials
No environment variables, credentials, or config paths are requested in metadata. The references appropriately state that you must authorize an Ahrefs account (OAuth/API key) via Ahrefs' own UI; that is expected and proportional for this integration.
Persistence & Privilege
Skill does not request always:true, does not require system config changes, and has no declared persistence or elevated privileges. It relies on the Ahrefs authorization flow and per-account API keys, which is appropriate.
Assessment
This skill appears coherent and focused on Ahrefs queries. Before installing: 1) Confirm you have an Ahrefs account and understand any API unit / plan limits (large queries can consume paid units). 2) Use the official OAuth/authorization flow — do not paste your raw API key into untrusted places. 3) Review the permissions requested at connect time and revoke the MCP connection from your Ahrefs account if you later want to disconnect. 4) If you consider the optional local MCP server, verify the referenced GitHub repo is the official ahrefs/ahrefs-mcp-server repository and inspect its code before deploying. 5) If you have sensitive data in queries, remember responses will come from Ahrefs and may include domain/backlink data; do not expose account credentials to third parties. Overall: installation is reasonable provided you trust Ahrefs and monitor API usage.

Like a lobster shell, security has layers — review code before you run it.

Current versionv1.0.0
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License

MIT-0
Free to use, modify, and redistribute. No attribution required.

SKILL.md

Ahrefs MCP

Access real-time Ahrefs SEO data directly through Model Context Protocol to analyze websites, research keywords, track rankings, and make data-driven SEO decisions.

First-Time Setup

If this is your first time using Ahrefs MCP, read references/setup.md for complete connection instructions. You'll need:

  • An Ahrefs account (Lite plan or higher)
  • To connect via the remote MCP server URL: https://api.ahrefs.com/mcp/mcp

After setup, return here for usage guidance.

Core Capabilities

Ahrefs MCP provides access to:

  1. Site Explorer - Domain metrics, backlinks, organic traffic, referring domains
  2. Keywords Explorer - Search volume, keyword difficulty, SERP analysis, related keywords
  3. Rank Tracker - Position tracking, visibility metrics, competitor rankings
  4. Site Audit - Technical SEO issues, crawl data, site health
  5. Content Explorer - Top performing content, content gaps

For detailed capability reference, see references/capabilities.md.

Usage Workflow

1. Understand the Request

Identify what SEO data is needed:

  • Domain/URL analysis → Site Explorer
  • Keyword data → Keywords Explorer
  • Position tracking → Rank Tracker
  • Technical SEO → Site Audit
  • Content ideas → Content Explorer

2. Query Ahrefs

Use natural language to request data. Examples:

"Get backlink profile for example.com"
"What's the search volume for 'best running shoes'?"
"Show me keyword difficulty scores for this list: [keywords]"
"Analyze competitor domains for example.com"
"Get current rankings from rank tracker project 'My Website'"

3. Analyze and Present

  • Present data in clear, actionable formats
  • Highlight key insights and opportunities
  • Suggest next steps based on findings
  • Cross-reference multiple data points when relevant

Common Workflows

Keyword Research + Cross-Reference

  1. User provides keyword list
  2. Query Ahrefs for each keyword's metrics (volume, difficulty, CPC)
  3. Present consolidated analysis
  4. Help prioritize based on criteria (difficulty vs. volume, intent, etc.)

See references/workflows.md for detailed workflow patterns.

Competitive Analysis

  1. Identify target domain and competitors
  2. Compare domain metrics (DR, organic traffic, referring domains)
  3. Analyze top organic keywords
  4. Identify content gaps
  5. Recommend opportunities

Site Audit Review

  1. Access site audit data for domain
  2. Identify critical issues by severity
  3. Prioritize fixes by impact
  4. Provide technical recommendations

When Ahrefs Connection is Missing

If the MCP connection is not configured:

  1. Provide setup instructions from references/setup.md
  2. Share the connection URL: https://api.ahrefs.com/mcp/mcp
  3. Guide through the authorization process
  4. Test connection before proceeding

API Limits Awareness

  • Each plan has row limits per request and monthly API unit caps
  • Track usage in Account settings → Limits and usage
  • Enterprise users can purchase additional units
  • Design efficient queries to conserve units

Best Practices

  • Be specific: Include target domain, date ranges, or specific metrics needed
  • Batch requests: When analyzing multiple keywords/domains, request data efficiently
  • Context matters: Cross-reference data points for deeper insights
  • Actionable output: Always provide recommendations, not just raw data
  • Verify before expensive queries: Confirm the scope before running large dataset requests

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