Image OCR Scraper

AI & Media Processing

Operated by Sourcelane✓ verified

A bulk OCR connector that extracts text, tables, formulas, and charts from images (screenshots, scanned documents, receipts, signs, menus, business cards, photos) using the PaddleOCR engine. Produces clean, structured text in Markdown (preserving headings, lists, tables) or structured JSON containing text blocks with bounding-box coordinates; supports printed and handwritten text, mixed-language content across 109 languages, rotated text and low-quality scans, and generates one output record per processed image for multi-image batch processing with rapid per-image processing.

Verified Sep 28, 3:55 AM

$0.03

per image

Up to 33 per call. Only pay for results returned; failed calls are refunded.

What people use it for

Document digitization: convert scanned PDFs, receipts, and invoices into searchable text
Data entry automation: extract structured data from forms, business cards, and ID documents
Screenshot analysis: capture text from app screenshots, error messages, or social media images
Translation pipelines: OCR foreign-language images for subsequent translation
Accessibility: generate text alternatives for image-based content
Compliance & search: enable full-text search across image-heavy archives

Trust & reliability

7d uptime trend

Window	Uptime	Success rate	p50	p95
24h	—	—	—	—
7d	—	—	—	—
30d	—	—	—	—

Calling contract

Call it through Sourcelane's gateway or MCP server. We run the connector, apply your agent's spend guardrails, and bill only the results returned.

Call it via Sourcelane

curl -X POST https://api.usesourcelane.com/v1/call \
  -H "Authorization: Bearer sl_live_your_agent_key" \
  -H "Content-Type: application/json" \
  -d '{"listing":"image-ocr-scraper","params":{"images":["https://dummyimage.com/600x100/fff/000.png&text=Hello+World+OCR+Test"]},"maxResults":10}'

Request params

Field	Type	Required	Description
`images`	array	optional	Images to OCR. Each entry must be a publicly accessible http/https URL or a base64 data URI (data:image/jpeg;base64,...).
`imageFiles`	array	optional	Upload image files directly. Combined with any URLs provided above.
`outputFormat`	string	optional	Markdown gives clean human-readable text with structure preserved. JSON returns structured data with text positions and bounding boxes for downstream processing.

Each result contains

Field	Type	Description
`inputImageUrl`	string	Input Image Url
`text`	string	Text
`outputFormat`	string	Output Format
`status`	string	Status
`error`	null	—

Use Image OCR Scraper from Claude, ChatGPT or Cursor

Pick your tool and connect in under a minute. Then just ask — for example: “Transcribe this video and give me timestamps for every product mention: <url>”

Connect Claude

Web, desktop and mobile. Paste one URL.

1Copy your personal connector URL
2In Claude open Settings → Connectors → Add custom connector
3Paste the URL and click Add — done

Manual setup (config files, REST, Python) +

Claude Code

Adds the Sourcelane MCP server with your key as a header.

terminal

claude mcp add --transport http sourcelane https://api.usesourcelane.com/mcp \
  --header "Authorization: Bearer sl_live_your_agent_key"

Claude Desktop (config file)

Alternative to the connector URL: add to claude_desktop_config.json, then restart Claude.

claude_desktop_config.json

{
  "mcpServers": {
    "sourcelane": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote",
        "https://api.usesourcelane.com/mcp",
        "--header",
        "Authorization:${AUTH_HEADER}"
      ],
      "env": {
        "AUTH_HEADER": "Bearer sl_live_your_agent_key"
      }
    }
  }
}

Cursor & Windsurf

Add to ~/.cursor/mcp.json (or Windsurf's mcp_config.json).

mcp.json

{
  "mcpServers": {
    "sourcelane": {
      "url": "https://api.usesourcelane.com/mcp",
      "headers": {
        "Authorization": "Bearer sl_live_your_agent_key"
      }
    }
  }
}

VS Code

Save as .vscode/mcp.json. VS Code prompts for your key once.

.vscode/mcp.json

{
  "servers": {
    "sourcelane": {
      "type": "http",
      "url": "https://api.usesourcelane.com/mcp",
      "headers": {
        "Authorization": "Bearer ${input:sourcelane-key}"
      }
    }
  },
  "inputs": [
    {
      "type": "promptString",
      "id": "sourcelane-key",
      "description": "Sourcelane agent key",
      "password": true
    }
  ]
}

ChatGPT Custom GPT (Actions)

Create a GPT → Actions → Import from URL, then Authentication: API Key, Bearer.

OpenAPI schema URL

https://usesourcelane.com/openapi.json

REST

One POST. Pass maxResults to cap cost.

curl

curl -X POST https://api.usesourcelane.com/v1/call \
  -H "Authorization: Bearer sl_live_your_agent_key" \
  -H "Content-Type: application/json" \
  -d '{"listing":"image-ocr-scraper","params":{"images":["https://dummyimage.com/600x100/fff/000.png&text=Hello+World+OCR+Test"]},"maxResults":10}'

Python, LangChain, CrewAI, OpenAI Agents SDK…

Wrap the REST call as a tool, or point an MCP client at the endpoint.

python

import requests

res = requests.post(
    "https://api.usesourcelane.com/v1/call",
    headers={"Authorization": "Bearer sl_live_your_agent_key"},
    json={
        "listing": "image-ocr-scraper",
        "params": {"images":["https://dummyimage.com/600x100/fff/000.png&text=Hello+World+OCR+Test"]},
        "maxResults": 10,
    },
    timeout=300,
)
body = res.json()
print(body["receipt"]["chargedMicros"], "micro-USD for", body["receipt"]["results"], "results")
print(body["data"])

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