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@ontosdk/mcp

Official Onto MCP server — clean Markdown and AIO scoring for any URL, available as MCP tools for Claude Code, Cursor, and any MCP client.

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Onto MCP Server

The official Onto Model Context Protocol server. Add clean web content reading and AI-readability scoring to Claude Code, Cursor, Cline, Zed, or any MCP-compatible AI client.

What this does

Onto's MCP server exposes these tools to any AI agent:

  • read_url — Read any URL and get back clean, agent-ready Markdown (typically 10× smaller than raw HTML)
  • score_url — Get the AIO (AI-readability) score for any URL with a breakdown of what helps and what hurts AI consumption
  • read_and_score — Both at once: clean content plus quality assessment so the agent knows how much to trust the source
  • batch — Read, score, or extract many URLs (an explicit list or a whole site) in one call
  • map_site — Discover a site's URLs via its sitemap, without reading them
  • extract_data — Return the structured data a page already declares (JSON-LD, OpenGraph, meta)

Every tool response ends with a one-line ⚡ Onto report — reduction, tokens saved, and AIO score — so the value is visible on every call.

This is the official MCP wrapper for the Onto Read API. It's a thin, deterministic layer: Onto cleans and scores with a rule-based engine (no LLM in the loop), so your agent's own model never has to parse raw HTML.

Why use this?

When AI agents read websites today, they parse hundreds of KB of React noise to find a few KB of actual content. This burns tokens and causes hallucinations.

Onto strips the noise server-side, returns the agent-ready format, and reports a confidence score for the source. One tool call, one accurate answer.

Quick start

1. Get an Onto API key

Sign up at app.buildonto.dev and create an API key at Read → Keys.

Free tier: 1,000 requests / month. No credit card.

2. Install in Claude Code

Add to your Claude Code MCP config:

{
  "mcpServers": {
    "onto": {
      "command": "npx",
      "args": ["-y", "@ontosdk/mcp@latest"],
      "env": {
        "ONTO_API_KEY": "onto_sk_live_your_key_here"
      }
    }
  }
}

Restart Claude Code. The Onto tools (read_url, score_url, read_and_score, batch, map_site, extract_data) will appear in the available tools list.

3. Install in Cursor

Add to Cursor's MCP configuration (Settings → Features → MCP):

{
  "mcpServers": {
    "onto": {
      "command": "npx",
      "args": ["-y", "@ontosdk/mcp@latest"],
      "env": {
        "ONTO_API_KEY": "onto_sk_live_your_key_here"
      }
    }
  }
}

See examples/ for Cline, Zed, and Continue configs.

4. Use it

In Claude Code or Cursor, try:

Read https://stripe.com/pricing using Onto and summarize the pricing tiers.

The agent calls read_url, gets clean Markdown, and returns an accurate summary without parsing hundreds of KB of layout HTML.

Tools

read_url

Returns clean Markdown for a URL with metadata about the extraction (sizes, reduction %, cache state).

Input:

FieldTypeRequiredDescription
urlstringyesPublicly accessible HTTP(S) URL
freshbooleannoIf true, bypass cache (default: false)

score_url

Returns the AIO (AI-readability) score for a URL — 0-100 with a letter grade, hallucination risk, and a structured list of penalties / benefits / recommendations.

Input:

FieldTypeRequiredDescription
urlstringyesURL to score

read_and_score

Returns clean Markdown plus the AIO score in one call. Recommended default for agentic workflows.

Input: same as read_url.

batch

Process many URLs in one call — billed as a single request, so you don't spend a credit per URL. Give an explicit list or a base URL whose pages are auto-discovered.

Input:

FieldTypeRequiredDescription
urlsstring[]one ofExplicit list of URLs (max 50). Use this or site.
sitestringone ofBase URL whose pages are auto-discovered via sitemap. Use this or urls.
mode"read" | "read-and-score" | "extract"noWhat to do per URL (default "read-and-score")
limitnumbernoSite mode only: max pages to discover (default 25, max 50)

map_site

Discover a site's URLs (sitemap → on-page links) without reading them. Cheap — use it to plan which pages to read or batch next.

Input:

FieldTypeRequiredDescription
urlstringyesBase URL of the site to map
limitnumbernoMax URLs to return (default 100, max 1000)

extract_data

Return the structured data a page already declares — JSON-LD, OpenGraph, and meta tags — plus the AIO score. Deterministic; no fields are inferred by a model.

Input:

FieldTypeRequiredDescription
urlstringyesURL to extract structured data from

Pricing

TierMonthly requestsPrice
Free1,000$0
Starter10,000$9
Growth100,000$49
Scale500,000$250
EnterpriseCustomContact sales

Manage your subscription at app.buildonto.dev/read/billing. Credit packs ($5–$200) are available for overflow once you're on a paid tier.

Configuration

Environment variables:

  • ONTO_API_KEY (required) — Your Onto API key from app.buildonto.dev/read/keys
  • ONTO_API_BASE (optional) — Override the API base URL (default: https://api.buildonto.dev)

Troubleshooting

"Invalid Onto API key"

Verify your key at app.buildonto.dev/read/keys. If you recently rotated keys, your MCP config may have a stale value.

"Monthly quota exceeded"

You've used your monthly allotment. Upgrade at app.buildonto.dev/read/billing or wait for the monthly reset. Paid tiers can also top up with credit packs.

Tool doesn't appear in Claude Code / Cursor

  • Verify the config file is valid JSON
  • Restart the MCP host (Claude Code, Cursor, etc.)
  • Check the host's MCP logs for connection errors
  • Make sure npx is on your PATH

"Request timed out"

The target site may be slow or unreachable. Onto's request timeout is 15 seconds. Retry, or try a different URL.

About Onto

Onto is the compatibility layer for the agent web. Three products on one engine:

  • Read (this MCP server + API) — AI developers read any URL cleanly
  • Serve (Next.js SDK) — Site owners serve clean Markdown to AI crawlers
  • Act (coming Q3 2026) — Agents act on websites through semantic intent

Built for AI agents reading the web. Built so they read it correctly.

License

MIT

Keywords

mcp

FAQs

Package last updated on 19 Jun 2026

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