sparrow84001/mcp-seo
by Various
mcp-seo is an AI-powered SEO and growth audit MCP server for modern web projects. It analyzes technical, on-page, AEO, GEO, local, and conversion issues, then generates safe, frame
MCP
sparrow84001/mcp-seo
Added 13 Sept 2026
Overview
mcp-seo is an MCP server that audits technical, on-page, AEO, GEO, local, and conversion issues for web projects. It generates framework-aware code fixes intended to improve visibility, performance, and business results. The server is written in TypeScript.
Best for
Best for
Developers who want automated SEO audits and code fixes inside an MCP-compatible assistant.
Use cases
- Run technical SEO audits on a web project
- Generate on-page and conversion issue fixes
- Identify AEO, GEO, and local search opportunities
How to use
Install
npx @sparrow84001/mcp-seo Tools exposed
seo_discover_projectseo_crawl_and_extractseo_audit_technicalseo_audit_onpageseo_audit_aeoseo_audit_geoseo_audit_localseo_audit_contentseo_audit_conversionseo_audit_performanceseo_audit_schemaseo_audit_internal_linksseo_generate_full_auditseo_generate_marketing_strategyseo_suggest_related_ecosystemseo_test_web_mcpseo_audit_sitemap_multipageseo_audit_robots_and_sitemapseo_generate_sitemap_and_robotsseo_generate_code_fix
Tested with
Claude Desktop, Cursor, Windsurf, ChatGPT
Notes
mcp-seo is an MCP server that audits technical, on-page, AEO, GEO, local, and conversion issues for web projects. It generates framework-aware code fixes intended to improve visibility, performance, and business results. The server is written in TypeScript.
0 stars on GitHub. Last updated 2026-09-07. Licensed MIT.
Use cases
- Run technical SEO audits on a web project
- Generate on-page and conversion issue fixes
- Identify AEO, GEO, and local search opportunities
Pros
- Covers a broad range of audit categories from technical to local and conversion
- Produces framework-aware code fixes rather than generic recommendations
- Integrates with MCP-compatible AI assistants for automated workflows
Cons
- No public stars or adoption evidence yet on GitHub
- Fix quality depends on the underlying AI model and project context
- Generated changes likely need manual review before deployment
Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.
Pros
- Covers a broad range of audit categories from technical to local and conversion
- Produces framework-aware code fixes rather than generic recommendations
- Integrates with MCP-compatible AI assistants for automated workflows
Cons
- No public stars or adoption evidence yet on GitHub
- Fix quality depends on the underlying AI model and project context
- Generated changes likely need manual review before deployment
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