Machine Shop – HTML Document Preparation

x402

Machine Shop – HTML Document Preparation is a paid API for AI agents from api.pay-forge.online, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-20).

Parses and chunks raw HTML into clean text, extracts entities (URLs, dates, money, emails, EVM addresses), and returns structured document metadata ready for downstream analysis.

Price / call$0.01

Seller volume →—

Success—

StatusUnknown

How this service works

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Output

Returns a JSON object containing: clean plain text, an array of overlapping text chunks with start/end character positions and index, a SHA-256 hash of the document, extracted entities (URLs, dates, money amounts, emails, EVM addresses), a markdown rendering, page metadata (title, description, language, canonical URL), any detected structured data, and a list of parser limitations.

Example use cases

Prep web page for RAG pipeline

“I have the raw HTML for a product documentation page — can you break it into 1000-character chunks with 100-character overlap and give me the clean text and any links so I can load it into my vector database?”

Extract financial figures from report HTML

“Here's the HTML of a quarterly earnings report — please pull out all the money amounts, dates, and any Ethereum addresses mentioned in it and return them as structured data.”

Convert HTML article to markdown

“Take this HTML blog post and convert it to clean markdown text, and also give me the page title, description, and language from the metadata.”

Technical details

Endpoint

POSThttps://api.pay-forge.online/v1/html-prepare-document?utm_source=zero.xyz

When to prefer

Choose this endpoint when you have raw HTML content in hand and need to prepare it for downstream tasks such as embedding, entity extraction, or evidence finding — particularly when you want chunked output with overlap for RAG pipelines. Prefer this over generic text extractors when you need EVM address extraction or SHA-256 document fingerprinting alongside standard NLP entities. Not suitable when you need JavaScript rendering, live web fetching, or scheduled monitoring.

Side effects

HTML exceeding 50,000 characters is rejected
JavaScript-rendered content will not be visible — only static HTML is processed
CSS-hidden elements may appear in output
No table reconstruction or microdata parsing — complex layouts lose structure
Invalid or malformed JSON body returns a 422 validation error
chunk_size below 64 or above 10,000 is rejected with a validation error

Input

Schema · Request body

Field	Type	Description
html	string
overlap	integer
base_url	string
chunk_size	integer

Output

Schema · Response

{
  "type": "json",
  "example": {
    "text": "Hello\nAgent documents.",
    "links": [],
    "document": {
      "text": "Hello\nAgent documents.",
      "chunks": [
        {
          "end": 22,
          "text": "Hello\nAgent documents.",
          "index": 0,
          "start": 0
        }
      ],
      "sha256": "ad5d70c4710c7e4d89fd61cc8a948080c97155017935a37327b3c88d4ed9f88f",
      "entities": {
        "urls": [],
        "dates": [],
        "money": [],
        "emails": [],
        "evm_addresses": []
      },
      "removed_duplicate_lines": 0
    },
    "markdown": "# Hello\n\nAgent documents.",
    "metadata": {
      "meta": {},
      "title": "Example",
      "language": "en",
      "canonical": "",
      "description": ""
    },
    "limitations": [
      "Static HTML only; no JavaScript, CSS visibility, article detection, table reconstruction or microdata parsing."
    ],
    "structured_data": []
  }
}

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