Links to PDFs

docs-scraper

CLI tool that scrapes documents from various sources into local PDF files using browser automation.

Installation

npm install -g docs-scraper

Quick start

Scrape any document URL to PDF:

docs-scraper scrape https://example.com/document

Returns local path: ~/.docs-scraper/output/1706123456-abc123.pdf

Basic scraping

Scrape with daemon (recommended, keeps browser warm):

docs-scraper scrape 

Scrape with named profile (for authenticated sites):

docs-scraper scrape  -p 

Scrape with pre-filled data (e.g., email for DocSend):

docs-scraper scrape  -D email=user@example.com

Direct mode (single-shot, no daemon):

docs-scraper scrape  --no-daemon

Authentication workflow

When a document requires authentication (login, email verification, passcode):

1. Initial scrape returns a job ID:

   docs-scraper scrape https://docsend.com/view/xxx
   # Output: Scrape blocked
   #         Job ID: abc123
   

2. Retry with data:

   docs-scraper update abc123 -D email=user@example.com
   # or with password
   docs-scraper update abc123 -D email=user@example.com -D password=1234
   

Profile management

Profiles store session cookies for authenticated sites.

docs-scraper profiles list     # List saved profiles
docs-scraper profiles clear    # Clear all profiles
docs-scraper scrape  -p myprofile  # Use a profile

Daemon management

The daemon keeps browser instances warm for faster scraping.

docs-scraper daemon status     # Check status
docs-scraper daemon start      # Start manually
docs-scraper daemon stop       # Stop daemon

Note: Daemon auto-starts when running scrape commands.

Cleanup

PDFs are stored in ~/.docs-scraper/output/. The daemon automatically cleans up files older than 1 hour.

Manual cleanup:

docs-scraper cleanup                    # Delete all PDFs
docs-scraper cleanup --older-than 1h    # Delete PDFs older than 1 hour

Job management

docs-scraper jobs list         # List blocked jobs awaiting auth

Supported sources

Scraper Reference

Each scraper accepts specific -D data fields. Use the appropriate fields based on the URL type.

DirectPdfScraper

Handles: URLs ending in .pdf

Data fields: None (downloads directly)

Example:

docs-scraper scrape https://example.com/document.pdf

DocsendScraper

Handles: docsend.com/view/*, docsend.com/v/*, and subdomains (e.g., org-a.docsend.com)

URL patterns:

Data fields:

| Field | Type | Description | |-------|------|-------------| | email | email | Email address for document access | | password | password | Passcode/password for protected documents | | name | text | Your name (required for NDA-gated documents) |

Examples:

# Pre-fill email for DocSend
docs-scraper scrape https://docsend.com/view/abc123 -D email=user@example.com
With password protection
docs-scraper scrape https://docsend.com/view/abc123 -D email=user@example.com -D password=secret123
With NDA name requirement
docs-scraper scrape https://docsend.com/view/abc123 -D email=user@example.com -D name="John Doe"
Retry blocked job
docs-scraper update abc123 -D email=user@example.com -D password=secret123

Notes:

NotionScraper

Handles: notion.so/*, *.notion.site/*

Data fields:

| Field | Type | Description | |-------|------|-------------| | email | email | Notion account email | | password | password | Notion account password |

Examples:

# Public page (no auth needed)
docs-scraper scrape https://notion.so/Public-Page-abc123
Private page with login
docs-scraper scrape https://notion.so/Private-Page-abc123 \
  -D email=user@example.com -D password=mypassword
Custom domain
docs-scraper scrape https://docs.company.notion.site/Page-abc123

Notes:

LlmFallbackScraper

Handles: Any URL not matched by other scrapers (automatic fallback)

Data fields: Dynamic - determined by Claude analyzing the page

The LLM scraper uses Claude to analyze the page HTML and detect:

Common dynamic fields:

| Field | Type | Description | |-------|------|-------------| | email | email | Login email (if detected) | | password | password | Login password (if detected) | | username | text | Username (if login uses username) |

Examples:

# Generic webpage (no auth)
docs-scraper scrape https://example.com/article
Webpage requiring login
docs-scraper scrape https://members.example.com/article \
  -D email=user@example.com -D password=secret
When blocked, check the job for required fields
docs-scraper jobs list
Then retry with the fields the scraper detected
docs-scraper update abc123 -D username=myuser -D password=secret

Notes:

Data field summary

| Scraper | email | password | name | Other | |---------|-------|----------|------|-------| | DirectPdf | - | - | - | - | | DocSend | ✓ | ✓ | ✓ | - | | Notion | ✓ | ✓ | - | - | | LLM Fallback | ✓* | ✓* | - | Dynamic* |

*Fields detected dynamically from page analysis

Environment setup (optional)

Only needed for LLM fallback scraper:

export ANTHROPIC_API_KEY=your_key

Optional browser settings:

export BROWSER_HEADLESS=true   # Set false for debugging

Common patterns

Archive a Notion page:

docs-scraper scrape https://notion.so/My-Page-abc123

Download protected DocSend:

docs-scraper scrape https://docsend.com/view/xxx
If blocked:
docs-scraper update  -D email=user@example.com -D password=1234

Batch scraping with profiles:

docs-scraper scrape https://site.com/doc1 -p mysite
docs-scraper scrape https://site.com/doc2 -p mysite

Output

Success: Local file path (e.g., ~/.docs-scraper/output/1706123456-abc123.pdf) Blocked: Job ID + required credential types

Troubleshooting

Scrape any document URL to PDF:

docs-scraper scrape https://example.com/document

Returns local path: ~/.docs-scraper/output/1706123456-abc123.pdf