Fetch Guard

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:

1. Pre-extraction sanitization removes hidden elements (display:none, visibility:hidden, opacity:0, font-size:0, transform:scale(0), clip:rect(0,0,0,0), zero-height overflow containers, and elements with matching foreground and background colors), elements hidden via CSS class/ID rules in <style> tags, off-screen positioned content, aria-hidden elements, <noscript> and <template> 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.
2. Pattern scanning runs a four-phase scan against the extracted text and metadata fields. Phase one applies 50 compiled regex patterns covering system prompt overrides, ignore-previous instructions, role injection, fake conversation tags, and hidden instruction markers, in English, Spanish, French, German, Japanese, Simplified Chinese, and Portuguese. Phase two normalizes the text via NFKC and confusable-character mapping, then rescans to catch homoglyph bypasses (Cyrillic or mathematical Unicode characters substituted for Latin, etc.). Phase three finds base64, hex-encoded, and URL percent-encoded blocks, decodes them, and scans against high-severity patterns. Phase four decodes the full document with ROT13 and scans against high-severity patterns. Metadata fields (title, description, og:title, etc.) are scanned independently with matches namespaced to their source field.
3. 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"]
    }
  }
}

Via Docker:

{
  "mcpServers": {
    "fetch-guard": {
      "command": "docker",
      "args": ["run", "-i", "--rm", "sterlsnyc/fetch-guard"]
    }
  }
}

Note: The Docker image does not include Playwright. JavaScript rendering (js: true) is not available when running via Docker. Use the uvx or pip install if you need JS rendering.

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. Also disables the automatic size guard
--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
--header KEY:VALUE	none	Custom HTTP header (repeatable)

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. Also disables the automatic size guard — use when you want explicit control over truncation without hitting the default limits
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	"domains" | "full"	"domains"	"domains" for unique external domains, "full" for all URLs with anchor text
auth_token	string	none	Bearer token for the Authorization header (e.g. "my-api-key"). Use for GitHub's authenticated API and other endpoints requiring auth
headers	object	none	Deprecated. Use auth_token instead. Will be removed in the next release

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:

1. /llms.txt preflight. 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.

2. 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.

3. 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).

4. 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.

5. 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.

6. HTML sanitization. Strips hidden elements (including extended CSS visibility techniques, color-matched text, and <template> tags), off-screen positioned content, aria-hidden nodes, <noscript> tags, and non-printing Unicode. Returns a tally of everything removed.

7. Content extraction. trafilatura converts sanitized HTML to markdown with link preservation.

8. Metadata extraction. Pulls title, author, date, description, canonical URL, and image from three sources in priority order: JSON-LD, Open Graph, then meta tags.

9. Link extraction. Two modes: domains returns a sorted list of unique external domains, full returns all external URLs grouped by domain with anchor text.

10. Injection scanning. Four-phase scan: original text against all 50 patterns (English + 6 additional languages), NFKC-normalized text for homoglyph bypasses, decode-and-scan for base64/hex/URL-percent-encoded payloads, and ROT13 whole-document scan. Metadata fields are scanned independently with matches namespaced to their source field. Each match records the pattern name, severity (high/medium), and a 60-character context snippet.

11. Size guard + truncation. By default, content over 2MB (pre-extraction) or 20KB (post-extraction) raises an error with a suggested max_words value. Setting --max-words disables both limits and truncates instead — use it when you want explicit control over what reaches the model.

12. Salt wrapping. The body gets wrapped in session-salted tags for defense-in-depth.

13. 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:

status, 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

status is a quick-glance summary string designed to be readable without expanding the full result:

"OK | html"
"HIGH | html | edge:paywall | sanitized:193 | retried | truncated:500"

Always includes risk and content_type. Non-default values (edge, sanitized > 0, retried, js, truncated) are appended only when present.

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, four-phase scan, metadata scan, merge API
│   ├── normalize.py        # NFKC + confusable-character normalization for homoglyph detection
│   ├── patterns.py         # 14 English + 36 multilingual compiled regex patterns — single source of truth
│   ├── multilingual_patterns.json  # Multilingual injection patterns (ES, FR, DE, JA, ZH, PT)
│   └── sanitizer.py        # Hidden element, CSS rule, color-match, 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.

Testing

The test suite has two tiers.

Unit tests (424, all mocked — no network calls):

pytest

Every module has a corresponding test file. CI runs the full suite on Python 3.10, 3.12, and 3.13 on every push and PR.

Live integration tests (54 entries, real network):

pytest -m live -v

Rather than hardcoded test functions, the live suite is data-driven: five YAML catalogs in tests/catalogs/ define URL entries with typed assertions. A single parametrized runner (test_catalog.py) evaluates all of them.

Catalog	Entries	What it covers
html.yaml	13	Metadata-rich pages, non-English content, redirects, government/academic sites
injection.yaml	9	OWASP cheat sheets, arXiv papers, controlled high-severity payload gist
edge_cases.yaml	10	Login walls (GitHub, Reddit, Steam), bot blocks (LinkedIn, Glassdoor, WSJ)
content_types.yaml	12	RSS/Atom feeds, GitHub API JSON, raw text files, XML sitemaps
llms_txt.yaml	11	Domains with /llms.txt (replaced vs. available), confirmed negatives

Live tests run automatically on release via a separate live-tests.yml workflow.

Development

# Run tests (414 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