mcpField
O
On-Page.ai SEO MCP

On-Page.ai SEO MCP

Local
api.on-page.aiBusiness & Marketing1Updated 15w ago

About On-Page.ai SEO MCP

On-Page.ai SEO MCP is a hosted MCP server for SEO work, giving AI agents structured search and page data. It supports page audits, competitor coverage comparisons, entity-gap analysis, internal-link opportunities, and report resources.

Key features

  1. 01Page SEO audits and recommendations
  2. 02Entity-gap and related-term analysis
  3. 03Competitor topic-coverage comparison
  4. 04Internal-link opportunity discovery
  5. 05Page-experience benchmarking
  6. 06Text or page topic classification

Use cases

  1. 01Review a page for a target keyword
  2. 02Compare competitors in search results
  3. 03Find missing entities and plan content edits
  4. 04Assess page experience and internal-link options

MCP support

The hosted MCP server provides SEO tools to MCP clients such as Codex, Claude Code, and ChatGPT over Streamable HTTP, and publishes report schemas and interpretation guides as MCP resources. Authentication supports OAuth or an API key bearer token.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

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-experience benchmarks.

On-Page.ai SEO MCP is a hosted Model Context Protocol server for search engine optimization work. It gives Codex, Claude Code, ChatGPT, and other AI agents access to structured SEO data for keyword research, competitor analysis, entity gaps, 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 it against 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. It helps agents review Google search results, compare SERP competitors, find entity gaps, improve organic visibility, and turn page-level SEO data into specific content recommendations.

The hosted MCP server works with Codex, Claude Code, ChatGPT, and other clients that 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

ToolUse
verify_installationZero-credit check that the server is connected, authenticated, and funded
scan_pageDefault full SEO audit for URL + keyword recommendations
scan_page_liteFaster entity and competitor-cohort scan
scan_page_deepDeeper competitor analysis and optional page-experience benchmark
classify_textCategorize a URL or text into topical buckets
check_jobCheck async job status
wait_for_jobWait for async job completion
get_job_resultFetch a completed job result
check_creditsCheck available credits and route costs

Scans can target 27 country-specific Google SERPs with the region parameter, and the server publishes report schemas and interpretation guides as MCP resources. Details: docs/tools.md.

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 assets also include:

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

Comments

Markdown supported

New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.