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apiacre.com Document Text & Metadata Extractor
x402
apiacre.com Document Text & Metadata Extractor is a paid API for AI agents from apiacre.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-09-13).
Extracts text content and metadata from common document file formats via a single POST call.
Price / call$0.01
Success—
StatusUnknown
How this service works
Extract clean text and metadata from supplied PDF, DOCX, HTML, Markdown, CSV, JSON, YAML, or plain-text documents.
Output
Returns the full extracted plain text from the document along with metadata fields such as title, author, creation date, page count, and detected file format.
Example use cases
Legal contract text extraction
“I have a PDF of a vendor contract — can you extract all the text and any metadata like author and page count so I can review its contents?”
Research paper ingestion pipeline
“Take this uploaded DOCX academic paper and extract all the text and metadata from it so I can index it in my knowledge base.”
Invoice data preprocessing
“I need to pull the raw text out of this scanned invoice PDF before I run it through my data parser — can you extract the text and any document metadata for me?”
Technical details
Endpoint
POSThttps://apiacre.com/v1/document/extractWhen to prefer
Choose this endpoint when you need to extract raw text and metadata from common document formats (PDF, DOCX, PPTX, etc.) as a preprocessing step before search, indexing, analysis, or storage. It is a good fit for agent pipelines that receive user-uploaded files and need programmatic access to document contents without building a parsing library. Prefer it over general-purpose OCR services when dealing with natively digital documents rather than scanned images.
Side effects
- Unsupported file format returns an error indicating the format is not handled
- Corrupted or password-protected files may fail to parse and return an extraction error
- Very large documents may time out or return partial results
- Missing or malformed input body returns a 400 validation error
- Empty documents return empty text with only metadata fields populated
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| filename | string | |
| content_base64 | string |
Output
Schema · Response
{
"type": "json",
"example": {
"data": {
"text": "Hello world",
"words": 2,
"metadata": {
"bytes": 11,
"sha256": "64ec88ca00b268e5ba1a35678a1b5316d212f4f366b2477232534a8aeca37f3c",
"filename": "report.txt"
},
"characters": 11
},
"meta": {
"cached": false,
"sources": [],
"warnings": [],
"duration_ms": 42,
"next_actions": [
{
"path": "/v1/document/redact",
"price": "$0.01",
"title": "PII and personal-data redaction",
"method": "POST",
"reason": "Remove common personal-data patterns from the extracted text before reuse.",
"service": "document.redact",
"use_output": "Use result.data.text as the redacted document and inspect the returned counts.",
"sample_path": "/samples/document.redact",
"handoff_path": "/catalog/document.redact",
"checkout_path": "/try/document.redact",
"input_template": {
"text": "$result.data.text"
},
"maximum_atomic_usdc": "10000",
"authorization_required": true,
"executes_automatically": false,
"handoff_payment_required": false
}
]
},
"service": "document.extract",
"version": "1",
"request_id": "018f1f54-7f38-7ba2-8dc3-5f90272d9f1a"
}
}Tags
x402
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