AutomateLab-tech/seo-performance-mcp

Overview

Post-publish SEO performance MCP that unifies signals from Google Search Console, Matomo, GA4, Clarity, and AI-citation sources per URL. It processes these inputs and emits a single per-URL verdict. Written in TypeScript, it is designed for integration into AI agent workflows.

Best for

Best for
Developers building AI agents that need automated post-publish SEO insights

Use cases

• Monitor SEO performance after publishing across multiple analytics platforms
• Get a unified SEO verdict per URL from disparate data sources
• Integrate SEO signals into AI-driven content optimization pipelines

How to use

Install

npx -y @automatelab/seo-performance-mcp

Tools exposed

• posts_list
• posts_snapshot
• posts_decay_curve
• posts_verdict
• posts_refresh_brief
• cohort_report
• posts_cite_loss
• gsc_quick_wins
• result-file
• audit_cohort
• find_quick_wins
• citation_loss_sweep

Tested with

Claude Desktop, Claude Code, Cursor, Continue

Notes

Post-publish SEO performance MCP that unifies signals from Google Search Console, Matomo, GA4, Clarity, and AI-citation sources per URL. It processes these inputs and emits a single per-URL verdict. Written in TypeScript, it is designed for integration into AI agent workflows.

0 stars on GitHub. Last updated 2026-05-31. Licensed MIT.

Use cases

• Monitor SEO performance after publishing across multiple analytics platforms
• Get a unified SEO verdict per URL from disparate data sources
• Integrate SEO signals into AI-driven content optimization pipelines

Pros

• Combines data from multiple analytics platforms into one verdict
• Provides a single per-URL SEO assessment
• Written in TypeScript for type safety and developer familiarity

Cons

• Zero stars indicates limited community adoption and validation
• Requires setup and maintenance of multiple analytics integrations
• Documentation and support may be sparse due to early stage

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.