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Onto

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by ravixalgorithm ยท TypeScript

Clean Markdown and AI-readability scoring for any URL. Built for AI agents.

The Onto MCP Server provides clean content extraction and AI-readability scoring for any URL, enabling AI agents to read and assess web content more efficiently. It exposes MCP tools for reading, scoring, and combining both operations, focusing on producing compact, agent-ready Markdown.

๐Ÿ› ๏ธ Key Features

  • read_url: converts any URL to clean, Markdown-formatted content
  • score_url: returns AI-readability score with explanations of strengths and weaknesses
  • read_and_score: combined workflow for clean content and quality assessment
  • designed for Claude Code, Cursor, Cline, Zed, and other MCP-compatible clients

๐Ÿš€ Use Cases

  • Convert web pages into compact, agent-ready Markdown
  • Analyze AI-readability of sources for better prompt construction
  • Integrate content reading and scoring into MCP-powered agents

โšก Developer Benefits

  • Lightweight, URL-based content processing for MCP ecosystems
  • Clear separation of reading and scoring tasks
  • Ready-to-use tooling for AI-agent pipelines and prompt engineering

โš ๏ธ Limitations

  • Behavior depends on input URL accessibility
  • Markdown output size and structure may vary by source content
  • Readability scores are guidance-based and not a formal standard

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