URL Visible Text Extraction API

Fetch a URL and extract only the text that would be visible to a sighted user: excluding hidden elements, scripts, styles, and nav boilerplate. Returns structured sections like a screen reader would present them. Available as a simple REST API — POST your input, get structured JSON back. 3 credits per call, no rate limiting, works in any language with HTTP support.

How it works

POST a JSON object with your input data to /v1/sense-url-screenshot-text. The API processes your request server-side using real computation (not mocked data) and returns a structured JSON response with your results and metadata including credits used and processing time.

Use cases

• Use URL Visible Text Extraction in automated pipelines without installing a library
• Call URL Visible Text Extraction from AI agent workflows via MCP or REST
• Integrate URL Visible Text Extraction into serverless functions with zero dependencies
• Build URL Visible Text Extraction functionality into any language that supports HTTP

API Reference

POST https://slopshop.gg/v1/sense-url-screenshot-text
Authorization: Bearer YOUR_API_KEY
Content-Type: application/json

Input parameters

Example response

{
  "data": {
    "result": "success",
    "processed": true
  },
  "meta": {
    "credits_used": 3,
    "engine": "real",
    "ms": 4
  }
}

Examples

Three real-world scenarios showing how developers use URL Visible Text Extraction in production.

curl -X POST https://slopshop.gg/v1/sense-url-screenshot-text \
  -H "Authorization: Bearer $SLOPSHOP_KEY" \
  -H "Content-Type: application/json" \
  -d '{"domain": "example.com"}'

curl -X POST https://slopshop.gg/v1/sense-url-screenshot-text \
  -H "Authorization: Bearer $SLOPSHOP_KEY" \
  -H "Content-Type: application/json" \
  -d '{"domain": "api.github.com"}'

curl -X POST https://slopshop.gg/v1/sense-url-screenshot-text \
  -H "Authorization: Bearer $SLOPSHOP_KEY" \
  -H "Content-Type: application/json" \
  -d '{"domain": "app.yourproduct.com"}'

Code examples

curl

curl -X POST https://slopshop.gg/v1/sense-url-screenshot-text \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"input": "your data here"}'

Python

import requests

response = requests.post(
    "https://slopshop.gg/v1/sense-url-screenshot-text",
    headers={"Authorization": "Bearer YOUR_API_KEY"},
    json={"input": "your data here"}
)
result = response.json()
print(result["data"])

Node.js

const response = await fetch("https://slopshop.gg/v1/sense-url-screenshot-text", {
  method: "POST",
  headers: {
    "Authorization": "Bearer YOUR_API_KEY",
    "Content-Type": "application/json"
  },
  body: JSON.stringify({ input: "your data here" })
});
const { data } = await response.json();
console.log(data);

CLI

# Install the Slopshop CLI
npm install -g slopshop

# Set your API key
export SLOPSHOP_KEY=your_api_key

# Call sense-url-screenshot-text
slop sense-url-screenshot-text '{"input": "your data here"}'

Pricing

Credits are purchased in bundles starting at $1 for 1,000 credits. All compute APIs like this one use 3 credits per call — that's $0.003. See all pricing tiers.

Related APIs in Sense: Web

• Fetch URL as Clean Text API — Fetch a URL and return clean readable text content, stripping all HTML tags, scripts, and styles. Returns the main textual content a human would read.
• Extract Links from URL API — Fetch a URL and extract all hyperlinks (href attributes), returning absolute URLs with their anchor text and whether they are internal or external.
• Get URL Metadata API — Fetch a URL and extract meta information: page title, meta description, Open Graph tags (og:title, og:image, og:description), Twitter card tags, and canonical URL.
• Detect Website Tech Stack API — Fetch a URL and detect technologies in use: JavaScript frameworks (React, Vue, Angular), CMS generators (WordPress, Ghost), analytics tools, CDNs, and server software from headers and HTML patterns.
• Measure URL Response Time API — Make multiple HTTP requests to a URL and return min, max, and average response times in milliseconds. Useful for detecting latency patterns and slowdowns.

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