Which integrations are available for this server?

Detects and handles Cloudflare bot challenges and status codes (403/429/503) to ensure successful content retrieval. Analyzes and strips elements hidden via CSS rules, class/ID signatures, or off-screen positioning to prevent hidden content attacks. Supports rendering and content extraction from JavaScript-heavy websites using an integrated Playwright-driven browser pipeline. Converts complex HTML and web content into clean, sanitized markdown while preserving essential structure and links. Automatically parses RSS and Atom feeds into structured summaries, enabling easy consumption of feed-based content. Sanitizes and normalizes content to remove 26 categories of non-printing characters and detect homoglyph-based prompt injection attempts. Provides specialized parsing for XML-based content, specifically targeting RSS and Atom feed summarization.

Fetch Guard

PyPI Python License: MIT

An MCP server and CLI tool that fetches URLs and returns clean, LLM-ready markdown. A purpose-built extraction pipeline sanitizes HTML, pulls structured metadata, detects prompt injection attempts, and handles the edge cases that break naive fetchers: bot blocks, paywalls, login walls, non-HTML content types, and pages that require JavaScript to render.

The core problem is straightforward: LLMs need web content, but raw HTML is noisy and potentially hostile. Fetched pages can contain hidden text, invisible Unicode, off-screen elements, and outright prompt injection attempts embedded in the content itself. This pipeline strips all of that before the content reaches the model.

Three layers handle the injection defense specifically:

Pre-extraction sanitization removes hidden elements (display:none, visibility:hidden, opacity:0), elements hidden via CSS class/ID rules in <style> tags, off-screen positioned content, aria-hidden elements, <noscript> tags, and 26 categories of non-printing Unicode characters including bidi isolates and Unicode Tags. This happens before content extraction, so trafilatura never sees the attack vectors.
Pattern scanning runs a three-phase scan against the extracted text. Phase one applies 14 compiled regex patterns covering system prompt overrides, ignore-previous instructions, role injection, fake conversation tags, and hidden instruction markers. Phase two normalizes the text via NFKC and confusable-character mapping, then rescans to catch homoglyph bypasses (Cyrillic characters substituted for Latin, etc.). Phase three finds base64 and hex encoded blocks, decodes them, and scans the decoded content with high-severity patterns.
Session-salted output wrapping generates a random 8-character hex salt per invocation and wraps the body in <fetch-content-{salt}> tags. Since the salt is unpredictable, injected content cannot spoof the wrapper boundaries.

One Tool

This is a single-tool MCP server. It exposes one tool — fetch — that runs a full extraction pipeline behind a consistent interface. No tool selection, no routing, no multi-step workflows. One URL in, one structured result out, configurable via parameters.

Quick Start

Prerequisites

Python 3.10+
pip

Install

pip install fetch-guard

For JavaScript rendering (optional):

pip install 'fetch-guard[js]' && playwright install chromium

Configure Your MCP Client

Add the following to your MCP client config. Works with Claude Code, Claude Desktop, Cursor, or any MCP-compatible client.

Via uvx (recommended):

{
  "mcpServers": {
    "fetch-guard": {
      "command": "uvx",
      "args": ["fetch-guard"]
    }
  }
}

Via pip install:

{
  "mcpServers": {
    "fetch-guard": {
      "command": "fetch-guard"
    }
  }
}

From source:

{
  "mcpServers": {
    "fetch-guard": {
      "command": "python",
      "args": ["-m", "fetch_guard.server"]
    }
  }
}

Verify

Ask your AI assistant to fetch any URL. If it returns structured content with a status header, metadata, and risk assessment, you're connected.

CLI

fetch-guard-cli <url> [options]
# or: python -m fetch_guard.cli <url> [options]

Flag	Default	Description
`--timeout N`	180	Request timeout in seconds
`--max-words N`	none	Word cap on extracted body content
`--js`	off	Use Playwright for JS-rendered pages
`--strict`	off	Exit code 2 on high-risk injection
`--links MODE`	`domains`	`domains` for unique external domains, `full` for all URLs with anchor text

Tool Parameters

The MCP fetch tool accepts these parameters:

Parameter	Type	Default	Description
`url`	string	required	The URL to fetch
`timeout`	integer	180	Request timeout in seconds. Ensures the tool always returns — no hanging fetches
`max_words`	integer	none	Word cap on extracted body content
`strict`	boolean	false	When true and high-risk injection is detected, the response is marked as an error
`js`	boolean	false	Use Playwright for JavaScript-rendered pages (requires `fetch-guard[js]`)
`links`	string	`"domains"`	`"domains"` for unique external domains, `"full"` for all URLs with anchor text

Claude Code Skill

Copy resources/fetch-guard/ to .claude/skills/fetch-guard/ in your project, or use the standalone command file resources/fetch-guard.md as a Claude Code command.

What It Does

The pipeline runs a 13-step sequence from URL to structured output:

/llms.txt Checks the domain root for /llms.txt before the full fetch. If the requested URL is a domain root and /llms.txt exists, that content replaces the normal HTML pipeline entirely. This respects the emerging convention for LLM-friendly site summaries.
Fetch. Static HTTP request via requests, or Playwright-driven browser rendering if --js is set. No automatic fallback between the two: --js is explicit opt-in.
Edge detection. Classifies the response for bot blocks (Cloudflare challenges, 403/429/503 with block signatures, LinkedIn's custom 999), paywalls (subscription prompts, premium overlays), and login walls (sign-in redirects, members-only patterns).
Automatic retry. Bot blocks trigger one retry with a full Chrome User-Agent string before reporting. Paywalls and login walls are reported immediately with no retry.
Content-type routing. Non-HTML responses get a fast path: JSON is rendered as a fenced code block, RSS/Atom feeds are parsed into structured summaries, CSV becomes a markdown table (capped at 2,000 rows), and plain text passes through directly. Binary content types are rejected.
HTML sanitization. Strips hidden elements, off-screen positioned content, aria-hidden nodes, <noscript> tags, and non-printing Unicode. Returns a tally of everything removed.
Content extraction. trafilatura converts sanitized HTML to markdown with link preservation.
Metadata extraction. Pulls title, author, date, description, canonical URL, and image from three sources in priority order: JSON-LD, Open Graph, then meta tags.
Link extraction. Two modes: domains returns a sorted list of unique external domains, full returns all external URLs grouped by domain with anchor text.
Injection scanning. Three-phase scan: original text against all 14 patterns, NFKC-normalized text for homoglyph bypasses, and decode-and-scan for base64/hex encoded payloads. Each match records the pattern name, severity (high/medium), and a 60-character context snippet.
Truncation. If --max-words is set, the body is truncated after extraction but before output wrapping.
Salt wrapping. The body gets wrapped in session-salted tags for defense-in-depth.
Output formatting. CLI produces five plaintext sections (status header, body, metadata, links, injection details). MCP server returns a structured JSON dict with the same data.

Output

CLI

Five sections, printed to stdout:

Status header: URL, fetch timestamp, risk flag (OK or INJECTION WARNING), sanitization tally, edge case info if detected
Body: clean markdown wrapped in <fetch-content-{salt}> tags
Metadata: JSON block with title, author, date, description, canonical URL, image
External links: domain list or full URL breakdown by domain
Injection details: pattern name, severity, and context snippet for each match (only present when patterns detected)

MCP Server

Returns a structured dict:

url, fetched_at, body, content_type, metadata, links, links_mode,
risk_level, injection_matches, edge_cases, sanitization,
llms_txt_available, llms_txt_replaced, js_rendered, js_hint,
retried, truncated_at

When --strict is set and the risk level is HIGH, the CLI exits with code 2 and the MCP server raises an error response. The full result is still available in both cases.

Exit Codes

Code	Meaning
0	Success
1	Fetch error (network failure, empty response, binary content)
2	High-risk injection detected (`--strict` only)

Architecture

fetch_guard/
├── pipeline.py             # Core orchestration — 13-step sequence, shared by CLI and server
├── cli.py                  # CLI entry point — arg parsing, pipeline call, output
├── server.py               # MCP server — FastMCP wrapper over the same pipeline
│
├── http/                   # HTTP fetching layer
│   ├── client.py           # Static HTTP fetch via requests
│   ├── playwright.py       # JS rendering via Playwright (optional)
│   └── llms_txt.py         # /llms.txt preflight check
│
├── extraction/             # Content extraction and edge detection
│   ├── content.py          # trafilatura wrapper — HTML to markdown
│   ├── content_type.py     # Non-HTML routing — JSON, XML/RSS, CSV, plain text
│   ├── edges.py            # Bot block, paywall, login wall classification
│   ├── links.py            # External link extraction (domain list or full URLs)
│   └── metadata.py         # JSON-LD, Open Graph, meta tag extraction
│
├── security/               # Injection defense
│   ├── guard.py            # Salt generation, content wrapping, three-phase pattern scanning
│   ├── normalize.py        # NFKC + confusable-character normalization for homoglyph detection
│   ├── patterns.py         # 14 compiled regex patterns — single source of truth
│   └── sanitizer.py        # Hidden element, CSS rule, and non-printing character removal
│
└── output/                 # Formatting
    └── formatter.py        # CLI output assembly

Each module is a single-responsibility unit with a public function as its interface. pipeline.py is the shared core: both cli.py and server.py call pipeline.run() and handle the result in their own way.

Development

# Run tests (239 unit tests, all mocked — no network calls)
pytest

# Run live integration tests (hits real URLs)
pytest -m live

# Lint
ruff check fetch_guard/ tests/

CI runs on push and PR to main via GitHub Actions, testing against Python 3.10, 3.12, and 3.13.

Acknowledgements

Developed with Claude Code.

License

MIT

fetch-guard