
Onto
io.github.ravixalgorithm由 GitHub 帳號 ravixalgorithm 發布v1.5.2更新於 Oct 24, 2026
Clean Markdown and AI-readability scoring for any URL. Built for AI agents.
概覽
Onto 可將任意網址讀取為乾淨的 Markdown、評估其 AI 可讀性並擷取結構化資料,讓助理無需解析原始 HTML 即可使用網頁內容。
- 可以做什麼
- 將網址讀取為適合代理使用的乾淨 Markdown,可選擇略過快取,並回傳體積縮減、快取狀態等擷取中繼資料。為網址的 AI 可讀性評分(0 到 100),給出等級、幻覺風險以及扣分項、加分項與改進建議。一次呼叫同時完成讀取與評分,建議作為代理工作流程的預設方式。依明確清單或透過網站地圖發現的整站頁面,批次讀取、評分或擷取多個網址。僅透過網站地圖與頁面連結探索網站網址,不讀取內容。擷取頁面已宣告的結構化資料,例如 JSON-LD、OpenGraph 與 meta 標籤。
- 適用情境
- 適合助理需要讀取、摘要或比較網頁,而原始 HTML 會浪費 token 或引入錯誤時;也適合在信任某個來源前先取得品質評分。需要一次呼叫瀏覽網站多個頁面時同樣適用。
- 執行需求
- 可使用遠端端點,或透過 npx 執行本機 npm 套件,因此需要 Node.js 與 npx。需要在 ONTO_API_KEY 中提供從 Onto 主控台取得的 API 金鑰;宣告要求 OAuth。ONTO_API_BASE 可覆寫 API 基礎位址。需要連線至 Onto API 及目標網站的網路存取。
安裝
在 SourceWeft 中
- 開啟 儀表板中的 Onto,將其新增到工作區。
- 連接 所需的 憑證。它們會被私密儲存,絕不會在公開頁面上展示。
- 為需要使用其工具的對話啟用該服務。
Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。
交給代理程式安裝
把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式,或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南,先向你展示發布者、端點和登入方式,經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。
閱讀 https://sourceweft.com/mcp/io.github.ravixalgorithm%2Fonto/install.md,並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前,先告訴我它的發布者、端點和登入方式,等我確認。不要把 API 金鑰寫進命令或我會提交的檔案;問我金鑰應從哪裡取得。其他 MCP 客戶端
把它新增到你客戶端的 mcpServers 設定中。 客戶端會在首次連接時完成 OAuth 登入。
{
"mcpServers": {
"onto": {
"type": "http",
"url": "https://api.buildonto.dev/mcp"
}
}
}README
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 consumptionread_and_score— Both at once: clean content plus quality assessment so the agent knows how much to trust the sourcebatch— Read, score, or extract many URLs (an explicit list or a whole site) in one callmap_site— Discover a site's URLs via its sitemap, without reading themextract_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 credits / month. No credit card.
2. Install in Claude Code
Add to your Claude Code MCP config:
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 the Onto server to ~/.cursor/mcp.json (all projects) or .cursor/mcp.json (this repo). Or use the UI: Customize (sidebar) → MCPs → add a custom server, same JSON.
Fully quit Cursor (Cmd+Q / Ctrl+Q) and reopen.
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:
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:
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. N credits — one per URL in the list after the list is known. Failed URLs (ok: false) are refunded. Default mode read-and-score is still N, not 2N. Give an explicit list or a base URL whose pages are auto-discovered.
Input:
map_site
Discover a site's URLs (sitemap → on-page links) without reading them. 1 credit per call (not per discovered URL) — use it to plan which pages to read or batch next.
Input:
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:
Pricing
MCP tool credits match the live API meter:
Connect / OAuth is not a debit.
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/keysONTO_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
npxis 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.
Links
- Onto homepage: buildonto.dev
- API documentation: docs.buildonto.dev
- Dashboard: app.buildonto.dev
- GitHub issues: github.com/ravixalgorithm/onto-mcp/issues
- Contact: [email protected]
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
來源:README.md,提交 ad70f63
工具
0版本歷史
1- v1.5.2最新Sep 16, 2026
評分
已滿足適用檢查項的 85%
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