fetchkit

AI-friendly web content fetching tool designed for LLM consumption. Rust library with CLI, MCP server, and Python bindings.

Features

• HTTP fetching - GET and HEAD methods with streaming support
• Pluggable fetchers - URL-aware dispatch to specialized handlers for repos, docs, feeds, videos, papers, and more
• HTML-to-Markdown - Built-in conversion optimized for LLMs
• HTML-to-Text - Plain text extraction with clean formatting
• Binary detection - Returns metadata only for images, PDFs, etc.
• Timeout handling - 1s first-byte, 30s body with partial content on timeout
• Safety limits - 10 MB default decompressed body cap with truncation
• URL filtering - URL-aware allow/block lists for controlled access
• SSRF protection - Resolve-then-check blocks private IPs by default
• MCP server - Model Context Protocol support for AI tool integration

Built-in Fetchers

FetchKit routes each request through an ordered fetcher registry. Specialized fetchers match first; the default fetcher handles everything else.

• GitHubCodeFetcher - GitHub source file URLs (/blob/...)
• GitHubIssueFetcher - GitHub issue and pull request URLs
• GitHubRepoFetcher - GitHub repository home pages
• TwitterFetcher - X/Twitter status URLs
• StackOverflowFetcher - Stack Overflow and Stack Exchange question URLs
• PackageRegistryFetcher - PyPI, crates.io, and npm package pages
• WikipediaFetcher - Wikipedia article URLs
• YouTubeFetcher - YouTube watch and youtu.be URLs
• ArXivFetcher - arXiv abstract and PDF URLs
• HackerNewsFetcher - Hacker News item threads
• RSSFeedFetcher - RSS and Atom feed URLs
• DocsSiteFetcher - docs sites with llms.txt/llms-full.txt support
• DefaultFetcher - all remaining HTTP/HTTPS URLs with HTML conversion, streaming, timeout handling, and binary detection

Installation

From crates.io (recommended)

cargo install fetchkit-cli

From Git

cargo install --git https://github.com/everruns/fetchkit fetchkit-cli

From Source

git clone https://github.com/everruns/fetchkit
cd fetchkit
cargo install --path crates/fetchkit-cli

CLI Usage

# Fetch URL (outputs markdown with frontmatter)
fetchkit fetch https://example.com

# Output as JSON instead
fetchkit fetch https://example.com -o json

# Custom user agent
fetchkit fetch https://example.com --user-agent "MyBot/1.0"

# Hardened outbound policy for cluster/data-plane use
fetchkit fetch https://example.com --hardened

# Show full documentation
fetchkit --llmtxt

Default output is markdown with YAML frontmatter:

---
url: https://example.com
status_code: 200
source_content_type: text/html; charset=UTF-8
source_size: 1256
---
# Example Domain

This domain is for use in illustrative examples in documents...

JSON output (-o json):

{
  "url": "https://example.com",
  "status_code": 200,
  "content_type": "text/html",
  "size": 1256,
  "format": "markdown",
  "content": "# Example Domain\n\nThis domain is for use in illustrative examples..."
}

MCP Server

Run as a Model Context Protocol server:

fetchkit mcp

# Hardened profile for cluster/data-plane use
fetchkit mcp --hardened

Exposes fetchkit tool over JSON-RPC 2.0 stdio transport. Returns markdown with frontmatter (same format as CLI). Compatible with Claude Desktop and other MCP clients.

Library Usage

Add to Cargo.toml:

[dependencies]
fetchkit = "0.2"

Basic Fetch

use fetchkit::{fetch, FetchRequest};

#[tokio::main]
async fn main() {
    let request = FetchRequest::new("https://example.com").as_markdown();

    let response = fetch(request).await.unwrap();
    println!("{}", response.content.unwrap_or_default());
}

With Tool Builder

use fetchkit::{FetchRequest, ToolBuilder};

let tool = ToolBuilder::new()
    .enable_markdown(true)
    .enable_text(false)
    .user_agent("MyBot/1.0")
    .allow_prefix("https://docs.example.com")
    .block_prefix("https://internal.example.com")
    .build();

let request = FetchRequest::new("https://example.com");
let response = tool.execute(request).await.unwrap();

Toolkit Contract Surface

use fetchkit::ToolBuilder;

let builder = ToolBuilder::new().enable_save_to_file(true);
let tool = builder.build();

assert_eq!(tool.name(), "web_fetch");
assert_eq!(tool.display_name(), "Web Fetch");

let definition = builder.build_tool_definition();
let mut service = builder.build_service();

Hardened Tool Profile

use fetchkit::Tool;

let tool = Tool::builder()
    .hardened()
    .allow_prefix("https://docs.example.com")
    .build();

Python Bindings

pip install fetchkit

from fetchkit_py import fetch, FetchRequest, FetchKitTool

# Simple fetch
response = fetch("https://example.com", as_markdown=True)
print(response.content)

# With configuration
tool = FetchKitTool(
    enable_markdown=True,
    user_agent="MyBot/1.0",
    allow_prefixes=["https://docs.example.com"]
)
response = tool.fetch("https://example.com")

Response Fields

Error Handling

Errors are returned in the error field:

• InvalidUrl - Malformed URL
• UrlBlocked - URL blocked by filter
• NetworkError - Connection failed
• Timeout - Request timed out
• HttpError - 4xx/5xx response
• ContentError - Failed to read body
• BinaryContent - Binary content not supported

Security

FetchKit blocks connections to private/reserved IP ranges by default, preventing SSRF attacks when used in server-side or AI agent contexts.

Blocked by default: loopback, private networks (10.x, 172.16-31.x, 192.168.x), link-local (169.254.x including cloud metadata), IPv6 equivalents, multicast, and other reserved ranges.

// Default: private IPs blocked (safe for production)
let tool = Tool::default();

// Explicit opt-out for local development only
let tool = Tool::builder()
    .block_private_ips(false)
    .build();

DNS pinning prevents DNS rebinding attacks. IPv6-mapped IPv4 addresses are canonicalized before validation. Redirects are followed manually in the default fetcher so each hop is revalidated against scheme and DNS policy. Allow/block prefixes are matched against parsed URLs rather than raw strings, which prevents lookalike host overmatches such as allowed.example.com.evil.test. Proxy environment variables are ignored by default. Use the hardened profile for cluster-facing deployments and opt in with ToolBuilder::respect_proxy_env(true) only when it is part of an intentional egress design.

See specs/threat-model.md for the full threat model. See docs/hardening.md for deployment guidance.

Configuration

Timeouts And Limits

• First-byte: 1 second (connect + initial response)
• Body: 30 seconds total
• Body size: 10 MB decompressed content by default

Partial content is returned on body timeout or body-size limit with truncated: true.

Binary Content

Automatically detected and returns metadata only for:

• Images, audio, video, fonts
• PDFs, archives (zip, tar, rar, 7z)
• Office documents

HTML Conversion

HTML is automatically converted to markdown:

• Headers: h1-h6 → # to ######
• Lists: Proper nesting with 2-space indent
• Code: Fenced blocks and inline backticks
• Links: [text](url) format
• Strips: scripts, styles, iframes, SVGs

License

MIT