arcfetch

Guide for using the arcfetch CLI to fetch web content, extract articles as clean markdown, and manage cached references.

Overview

arcfetch converts web pages to clean markdown with:

• Automatic Playwright fallback when simple HTTP fetch produces low-quality results
• Quality scoring (0-100) with boilerplate/error page/login wall/paywall detection
• Content-to-source ratio analysis to catch JS-rendered or gated content
• Anti-bot detection measures (stealth plugin, viewport/timezone rotation, realistic headers)

Installation

# Use via bunx (no install needed)
bunx arcfetch <command>

# Or install globally
bun install -g arcfetch

Commands

fetch

Fetch a URL and save extracted markdown to the temp folder.

arcfetch fetch <url> [options]

Options:

• -q, --query <text> – Search query (saved as metadata)
• -o, --output <format> – Output format:
  • text – Plain text, LLM-friendly (default)
  • json – Structured JSON
  • path – Just the filepath
  • summary – slug|filepath format
• --pretty – Human-friendly output with emojis
• -v, --verbose – Show detailed output (quality scores, pipeline decisions)
• --min-quality <n> – Minimum quality score 0-100 (default: 60)
• --temp-dir <path> – Temp folder (default: .tmp/arcfetch)
• --docs-dir <path> – Docs folder (default: docs/ai/references)
• --wait-strategy <mode> – Playwright wait: networkidle (default), domcontentloaded, load
• --force-playwright – Skip simple fetch, use Playwright directly
• --refetch – Re-fetch even if URL already cached

Examples:

# Basic fetch (plain text output for LLMs)
arcfetch fetch https://example.com/article

# Get just the filepath
arcfetch fetch https://example.com -o path

# Human-friendly output
arcfetch fetch https://example.com --pretty

# JSON output for scripting
arcfetch fetch https://example.com -o json

# With search query metadata
arcfetch fetch https://example.com -q "search term"

# Verbose mode to see pipeline decisions
arcfetch fetch https://example.com -v

# Force Playwright for JS-heavy sites
arcfetch fetch https://example.com --force-playwright

Quality Pipeline:

1. Simple HTTP fetch with browser-like User-Agent
2. Extract content with Readability + Turndown
3. Quality score (0-100) with boilerplate detection
4. Score >= 85: accept as-is
5. Score 60-84: try Playwright, use whichever scores higher
6. Score < 60: require Playwright, fail if still below threshold

list

List all cached references.

arcfetch list [options]

Options:

• -o, --output <format> – Output format: text, json
• --pretty – Human-friendly output

arcfetch list --pretty
arcfetch list -o json

links

Extract all links from a cached reference.

arcfetch links <ref-id> [options]

Options:

• -o, --output <format> – Output format: text, json
• --pretty – Human-friendly output

arcfetch links my-article --pretty
arcfetch links my-article -o json

fetch-links

Fetch all links from a cached reference (parallel, max 5 concurrent).

arcfetch fetch-links <ref-id> [options]

Options:

• --refetch – Force re-fetch even if already cached
• -o, --output <format> – Output format: text, json
• --pretty – Human-friendly output

arcfetch fetch-links my-article --pretty

promote

Move reference from temp to permanent docs folder.

arcfetch promote <ref-id> [options]

arcfetch promote my-article --pretty
arcfetch promote my-article -o json

delete

Delete a cached reference.

arcfetch delete <ref-id> [options]

arcfetch delete my-article --pretty

config

Show current configuration.

arcfetch config

mcp

Start the MCP server (for Claude Code integration).

arcfetch mcp

Workflow Patterns

Single Article

arcfetch fetch https://example.com/guide --pretty
cat .tmp/arcfetch/example-guide.md  # Review content
arcfetch promote example-guide      # Move to docs if good

Batch Fetch

for url in "url1" "url2" "url3"; do
  arcfetch fetch "$url" --pretty
done
arcfetch list --pretty         # Review all
arcfetch promote my-article    # Promote desired ones

Fetch All Links from a Page

arcfetch fetch https://example.com/resources --pretty
arcfetch links resources --pretty           # See what links exist
arcfetch fetch-links resources --pretty     # Fetch them all

Scripting with JSON Output

RESULT=$(arcfetch fetch https://example.com -o json)
REF_ID=$(echo "$RESULT" | jq -r '.refId')
QUALITY=$(echo "$RESULT" | jq -r '.quality')

if (( QUALITY >= 85 )); then
  arcfetch promote "$REF_ID"
fi

Cleanup

arcfetch list --pretty
arcfetch delete unwanted-ref

Configuration

Priority Order

1. CLI arguments
2. Environment variables
3. arcfetch.config.json
4. .arcfetchrc / .arcfetchrc.json
5. Built-in defaults

Config File (arcfetch.config.json)

{
  "quality": {
    "minScore": 60,
    "jsRetryThreshold": 85
  },
  "paths": {
    "tempDir": ".tmp/arcfetch",
    "docsDir": "docs/ai/references"
  },
  "playwright": {
    "timeout": 30000,
    "waitStrategy": "networkidle"
  }
}

Environment Variables

export SOFETCH_MIN_SCORE=60
export SOFETCH_TEMP_DIR=".tmp/arcfetch"
export SOFETCH_DOCS_DIR="docs/ai/references"

Quality Scoring

Score starts at 100 and deductions apply:

Boilerplate patterns detected (on short content < 2000 chars):

• Error pages: “something went wrong”, “an error occurred”, “unexpected error”
• 404 pages: “page not found”, “404 not found”
• Login walls: “log in to continue”, “please log in”, “sign in to continue”
• Paywalls: “subscribe to continue reading”
• Bot detection: “are you a robot”, “complete the captcha”, “verify you are human”
• Access denied, JS-required, unsupported browser pages

Score thresholds:

• >= 90: Excellent
• >= 75: Good
• >= 60: Acceptable (minimum to pass)
• < 60: Poor (rejected)

MCP Server

The MCP server exposes 6 tools for Claude Code integration:

Start via CLI: arcfetch mcp

Or configure in Claude Code MCP settings to run bunx arcfetch as stdio server.

File Format

Cached files use markdown with YAML frontmatter:

---
title: "Article Title"
source_url: https://example.com/article
fetched_date: 2026-02-06
type: web
status: temporary
query: "optional search query"
---

# Article Title

Extracted markdown content...

• Ref IDs are slugified titles (e.g., how-to-build-react-apps)
• Temp storage: .tmp/arcfetch/<slug>.md (status: temporary)
• Permanent storage: docs/ai/references/<slug>.md (status: permanent, after promote)
• Duplicate detection: re-fetching same URL returns existing ref unless --refetch

References

• Package: https://www.npmjs.com/package/arcfetch
• Repository: https://github.com/briansunter/arcfetch
• MCP Protocol: https://modelcontextprotocol.io