Package Information
Released: this month
Downloads: 0 weekly / 0 monthly
Latest Version: 0.2.1
Author: The Quite Good Project
Available Nodes
Documentation generating…
Documentation
n8n-nodes-tokenmarkdown
An official n8n community node for TokenMarkdown. Strip 90% to 95% of HTML bloat, cookie banners, tracking iframes, and scripts from any webpage or PDF, converting raw web content into pure, LLM-ready Markdown before sending it into your AI workflows.
⚡ Why Use TokenMarkdown in n8n?
Sending raw HTML or generic scraping output directly into OpenAI, Anthropic, or Gemini burns massive token budgets and pollutes LLM context windows with junk:
- Slash Token Bills by 85–95%: A standard documentation or blog page is often 200KB–800KB of raw HTML (~50k–200k tokens). TokenMarkdown extracts the semantic core, delivering 2k–5k tokens.
- Eliminate Context Pollution: Prevents hallucinations caused by cookie consent banners, header navigation links, ads, footer disclaimers, and embedded scripts.
- Deterministic AST Extraction: Powered by an Abstract Syntax Tree (AST) parsing engine designed specifically for RAG embeddings and LLM ingestion.
- Zero Runtime Dependencies: The node has zero external runtime dependencies (
dependencies: {}), ensuring rapid execution and rock-solid stability in both cloud and self-hosted n8n environments.
📦 Installation
Via n8n Community Nodes (Recommended)
- In your n8n workspace, navigate to Settings > Community Nodes.
- Click Install.
- Enter
n8n-nodes-tokenmarkdownin the npm package name field. - Agree to the risks of installing community packages and click Install.
Via Docker / Self-Hosted CLI
In your n8n root directory (or container custom directory):
npm install n8n-nodes-tokenmarkdown
🔑 Authentication & Pricing
TokenMarkdown works immediately with zero configuration:
- Anonymous Free Trial: 10 free extractions out of the box (leave credentials empty).
- Developer Starter Tier: Enter your developer work email in credentials to unlock 100 free requests (no credit card required).
- Starter Credit Pack ($10 one-time): 5,000 non-expiring extractions with zero monthly commitment. Buy 1-Click Starter Pack
- Production API Key: For production pipelines and high-volume workloads:
- Builder ($29/mo): 2,500 extractions / month. Subscribe here
- Growth ($79/mo): 10,000 extractions / month. Subscribe here
- Scale / Agency ($199/mo): 40,000 extractions / month.
To configure credentials in n8n:
- Go to Credentials > New Credential.
- Search for TokenMarkdown API.
- Enter your API Key (or enter your Developer Email for free tier scaling).
🚀 Node Operations & Parameters
Operation: Extract Clean Markdown
| Parameter | Type | Required | Description |
|---|---|---|---|
| Target URL | String | Yes | The URL of the webpage or PDF to extract and convert. |
| Extraction Mode | Options | No | Compression strategy: • Article Only (Default): Aggressively strips nav/footer chrome for maximum token savings (~90-95%). • Full Page: Preserves page layout hierarchy while stripping ads/scripts. • Raw Semantic HTML: Sanitized semantic HTML tags without converting to Markdown. |
| Include Images | Boolean | No | Retain markdown image embeds (). Default: false. |
| Include Links | Boolean | No | Retain markdown hyperlinks ([text](url)). Default: true. |
| Include Table of Contents | Boolean | No | Auto-generate a markdown TOC at the top. Default: false. |
| CSS Selector Filter | String | No | Target a specific container (e.g. article.docs-body, #main-content). |
📊 Output Data Structure
The node outputs a structured JSON object ready for immediate chaining with AI Agent, Vector Store, or HTTP nodes:
{
"markdown": "# Stripe API Reference\n\nThe Stripe API is organized around REST...",
"title": "Stripe API Reference",
"excerpt": "Complete reference documentation for the Stripe REST API.",
"byline": "Stripe Engineering",
"url": "https://docs.stripe.com/api",
"tokens": 3420,
"rawTokens": 78900,
"reductionPercentage": 95.66,
"latencyMs": 342
}
🛠️ Example Workflows
- RAG Pipeline:
Webhook➔TokenMarkdown➔Text Splitter➔Qdrant / Pinecone Vector Store - Autonomous Research Agent:
Google Search➔TokenMarkdown➔AI Agent (GPT-4o / Claude 3.5 Sonnet) - Competitor Changelog Tracker:
Schedule Trigger➔TokenMarkdown➔Slack / Discord Notification
📄 License & Attribution
- License: MIT
- Author: The Quite Good Project
- Support & Security:
engineering@quitegoodproject.com