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On-Page.ai SEO MCP

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On-Page.ai SEO MCP server for search engine optimization work with Codex and Claude Code. Public docs, examples, and directory metadata for the hosted server.

On-Page.ai SEO MCP

On-Page.ai SEO MCP banner

Hosted MCP server for evidence-backed on-page SEO audits, entity-gap analysis,competitor coverage checks, internal-link opportunities, and page-experiencebenchmarks.

On-Page.ai SEO MCP is a hosted Model Context Protocol server for search engineoptimization work. It gives Codex, Claude Code, ChatGPT, and other AI agentsaccess to structured SEO data for keyword research, competitor analysis, entitygaps, on-page audits, and search-result recommendations through one MCP server.

Demo

https://github.com/user-attachments/assets/4b2ab1ff-b5bf-4262-a3ad-0e987a34376d

Server

https://api.on-page.ai/mcp

What It Does

On-Page.ai MCP workflow

On-Page.ai gives AI agents structured SEO evidence before they recommend edits.Instead of generic SEO advice, the agent can scan the live URL and compare itagainst the current search-result cohort for a keyword.

Core workflows:

  • Find missing entities and related terms
  • Compare competitor topic coverage
  • Generate internal-link candidates
  • Benchmark page experience against top ranking competitors
  • Classify page or text topical focus
  • Return customer-safe structured reports for agent reasoning

Use Cases

Use On-Page.ai SEO MCP as part of SEO tools and SEO workflows for AI agents. Ithelps agents review Google search results, compare SERP competitors, find entitygaps, improve organic visibility, and turn page-level SEO data into specificcontent recommendations.

The hosted MCP server works with Codex, Claude Code, ChatGPT, and other clientsthat support MCP setup, API-key authentication, or remote server integrations.

API Homepage

On-Page.ai API homepage screenshot

The public API homepage shows the product surface behind the hosted MCP server.

Available Tools

Tool Use
scan_page Default full SEO audit for URL + keyword recommendations
scan_page_lite Faster entity and competitor-cohort scan
scan_page_deep Deeper competitor analysis and optional page-experience benchmark
classify_text Categorize a URL or text into topical buckets
check_job Check async job status
wait_for_job Wait for async job completion
get_job_result Fetch a completed job result
check_credits Check available credits and route costs

Quick Install

Most users should start here:

https://api.on-page.ai/install

Client-specific docs are also included in docs/install.md.

Example Prompts

Use On-Page.ai to scan https://example.com/page for "target keyword".
Return the top missing entities, explain why they matter, and suggest minimal
edits to existing sentences.

Run a deep On-Page.ai scan for https://example.com/page with keyword
"target keyword". Compare the recurring competitor gaps and prioritize the
fixes that are most likely to improve relevance.

More examples: examples/prompts.md

Directory Submission Assets

MCP directory metadata lives in:

  • .cursor-plugin/plugin.json
  • mcp.json
  • server.json
  • metadata/directory-submission.json
  • docs/directory-listing.md

Cursor plugin assets also include:

  • skills/on-page-seo/SKILL.md
  • assets/generated/on-page-ai-logo-400.png

Safety Boundary

This repo should only contain public-facing material. If you are contributing,read SECURITY.md and do not include:

  • private source code
  • environment files
  • deployment notes
  • credentials or tokens
  • customer data
  • internal admin URLs
  • internal review packages
  • generated debug output

Support

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