._____   _  __   __  _____   ____        _____   ____     _   ____ 
|  ___| | | \ \ / / |  ___| |  __ \     / ____| |  __ \  | | |  __ \  
| |__   | |  \ V /  | |__   | |__) |   | |  __  | |__) | | | | |__) |  
|  __|  | |   > <   |  __|  |  _  /    | | |_ | |  _  /  | | |  ___/  
| |     | |  / ^ \  | |___  | | \ \    | |__| | | | \ \  | | | |     
|_|     |_| /_/ \_\ |_____| |_|  \_\    \_____| |_|  \_\ |_| |_|       
  

> [TARGET DETECTED]. CONNECTING TO NODE...
> STRIPPING DOM BLOAT & ADS...
> EXTRACTING HIGH-SIGNAL MARKDOWN VECTORS...
> STATUS: READY FOR BREACH
>

🟢 0% Developer Markup — You only pay for raw Apify compute units.

Fixer Grip — Web to Markdown for LLMs & RAG 🦾

Extract clean, high-signal Markdown from dynamic websites. Built specifically for AI agent pipelines, RAG context windows, and vector databases — without HTML bloat, scripts, or intrusive ads.

⚡ Key Features

• Zero HTML Noise: Strips out navigation, sidebars, footers, scripts, and clutter, leaving only core text.
• LLM & RAG Ingestion Ready: Clean Markdown formatting optimized for OpenAI, Anthropic, and vector storage (Pinecone, Chroma, LlamaIndex).
• Structured Outbound Links: Automatically isolates and extracts hyperlinks into clean JSON, making downstream graph building and recursive LLM agent navigation effortless.
• Dynamic Content Penetration: Smart auto-scrolling to capture lazy-loaded and SPA content.
• Traffic & Speed Booster: Optional image and media blocking to accelerate page rendering and LLM response time.
• Stealth Operations: Full proxy integration (Datacenter & Residential) to bypass rate limits and basic blockades.
• Dev-First Sanitization: Fixer Grip natively protects <pre> and <code> blocks. Technical documentation, code snippets, and inline syntax maintain 100% structural integrity for optimal LLM context chunks.

🤖 MCP Ready (Model Context Protocol)

This actor is fully compatible with the Apify MCP server. You can plug it directly into Claude Desktop, Cursor, or any custom AI agent to give your LLM instant, clean URL-to-Markdown extraction capabilities during RAG workflows without manual scripts.

🛑 Scope & Boundaries

• Focused Single-Page Extraction: Designed for fast, targeted single-page markdown parsing to deliver zero-noise, deterministic context chunks for RAG nodes and AI Agents.
• Custom Crawling & Pagination: Domain-level pagination or recursive spider crawling can be configured upon request or provided as a custom build.

---

💰 Pricing & Free Tier

Fixer Grip is 100% free to run. There are no platform markups, subscription fees, or paywalls for single-page extractions.

You only use standard Apify Compute Units (PPCU) from your own account.

💡 Testing on Apify's Free Tier? Apify provides a default $5/month credit for every free account — this covers thousands of single-page extractions with Fixer Grip every month without attaching a credit card.

⚡ Need Mass Crawling, Sitemap Processing, or Custom Pipelines?

The public version of Fixer Grip is restricted to 1 URL per execution for high-speed single-page testing and RAG pipeline step-runs.

If you need:

• 📦 Batch processing (thousands of URLs or sitemaps)
• 🕸️ Domain-level crawling & pagination
• 🔑 Dedicated private instances & custom API builds

📩 Reach out via email: kira.data.arch@gmail.com to get access to a private build or a custom dump.

🔑 What's inside the Private B2B Build / Custom API?

• 📦 Batching & Sitemaps: Supply arrays of URLs, domain-level crawlers, or sitemap.xml.
• ⚡ Granular Performance Tuning: Full control over DOM size caps (max_html_size_mb), custom scroll depths (max_scrolls), and precise harvest timeouts (max_harvest_time).
• 🧹 Custom Media & Noise Filters: On-the-fly stripping of media artifacts, ads, or bespoke DOM nodes before RAG ingestion.

💡 The RAG ROI Factor

Raw HTML junk (scripts, navbars, footers) bloats downstream OpenAI / Anthropic prompt context. By stripping DOM noise before context ingestion, Fixer Grip cuts token payload size by up to 80% — saving tens of dollars on LLM API costs and preventing context window truncation.

---

📥 Input Schema Example

{
  "startUrls": [
    { "url": "https://docs.apify.com/" }
  ],
  "remove_media_tags": true,
  "remove_commercial_noise": true
}

🎯 Per-URL Overrides via userData

You can override selector and kill_list for individual target nodes by passing them inside the userData object of any URL in startUrls:

{
  "startUrls": [
    {
      "url": "https://example.com/blog/post-1",
      "userData": {
        "selector": "main.article-body",
        "kill_list": [".ad-box", ".social-share"]
      }
    }
  ]
}

---

📤 Output Format

The Actor pushes structured dataset items containing status info, clean Markdown text, error details, and isolated outbound links:

Successful Extraction (BREACH_SUCCESS):

{
  "target": "https://www.theverge.com/",
  "success": true,
  "status": "BREACH_SUCCESS",
  "intel_type": "NEURAL_MD",
  "payload": "# The Verge\n\nClean text content goes here...",
  "outbound_links": [
    {
      "text": "Skip to main content",
      "url": "https://www.theverge.com"
    },
    {
      "text": "Subscribe",
      "url": "https://www.theverge.com/subscribe"
    }
  ],
  "error": null,
  "timestamp": 1786020530
}

Failed / Blocked Attempt (BREACH_FAILED):

{
  "target": "https://example.com/protected",
  "success": false,
  "status": "ACCESS_DENIED",
  "intel_type": "ERROR_REPORT",
  "payload": null,
  "outbound_links": null,
  "error": {
    "code": 403,
    "reason": "Target presented anti-bot challenge or rate limit.",
    "trace_url": "https://api.apify.com/v2/key-value-stores/..."
  },
  "timestamp": 1786020530
}

---

💡 Best Used For

• Training datasets & Knowledge Graph creation
• RAG pipelines for AI Agents & Vector DBs
• Clean web documentation ingestion

---

🚀 Active Beta & Support

Fixer Grip is in active rollout. We continuously tune layout heuristics, edge-case spatial cleanup, and SPA hydration handlers.

• ⚡ Fast Bugfix Priority: Found a site where layout breaks or junk leaks through? Open a report in the Issues tab — edge-case patches are usually shipped within 24–48 hours.
• 🎯 Custom Rules & Pipelines: Need dedicated extraction logic, custom selector presets, or specific output formats for your agent workflow? Drop a note in the Issues section — we tune custom handles for active users.

⭐️ Support & Feedback

If Fixer Grip saved your compute credits or cut down your LLM context token size, drop a star on Apify! Found a tough site that resists extraction? Open an Issue — edge cases are usually patched within 24–48 hours.

🧠 ChatGPT Evaluation of MCP server

I tested Fixer-Grip on static pages, large Wikipedia content, technical documentation (MDN), JavaScript-generated content, and infinite-scroll pages.

Parameter	Rating
Content extraction	⭐⭐⭐⭐⭐
Markdown & structure	⭐⭐⭐⭐⭐
Dynamic content	⭐⭐⭐⭐½
Noise removal	⭐⭐⭐⭐⭐
Content preservation	⭐⭐⭐⭐
Technical pages	⭐⭐⭐⭐⭐
Links & metadata	⭐⭐⭐⭐⭐
Custom control (selector, kill_list)	⭐⭐⭐⭐⭐
Speed (with warm container)	⭐⭐⭐⭐
Overall	⭐⭐⭐⭐½ / 5

Verdict

Highly usable for LLM/RAG web extraction.

Fixer-Grip does an excellent job of turning complex web pages into clean, structured Markdown while preserving links, tables, code, and dynamically loaded content.

Its main weakness is aggressive heuristic extraction: on poorly structured pages, legitimate content can occasionally be classified as noise. The selector and kill_list controls provide a useful way to override the automatic extraction when precision matters.

Overall: 8.5/10 — a genuinely useful extraction layer between the web and an LLM.

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      '-.  ⬬  .-'         
         ╰---╯  
         
[ SYSTEM STATUS: OPERATIONAL // READY FOR BREACH ]