Spider - High-Performance Web Crawler and Scraper in Rust

Get web data for AI agents and LLMs with a concurrency-first, streaming crawler that renders JavaScript on demand.

Source repo
spider-rs/spider
Stars
★ 2.8k
Last updated
today
License
MIT
Primary language
Rust

At a glance

How it runs
Library / SDKCLIMCP server
Works with
Platform-specific
Cost
Free tier plus a paid hosted plan
Setup effort
Low · running in minutes
You'll need
RustCargoShell / CLINetwork accessLocal filesystem
Typical use
AI/LLM developers extracting web data from large volumes of pages to feed vector stores for RAG pipelines.
Not a fit if
  • Teams that need fully offline crawling with no cloud service
  • Teams unwilling to pay for anti-bot unblocking
  • Non-Rust developers, since other languages may have limited features

What does this agent do, and when should you use it?

Spider is a concurrency-first web crawling engine written in Rust, designed to quickly crawl and stream web data. It prioritizes HTTP requests and only launches headless Chrome when a page requires JavaScript, improving efficiency. The project offers a Rust library, CLI, Node.js and Python packages, and supports managed crawling via Spider Cloud. The engine includes built-in concurrency, rate limiting, retries, proxies, and stealth features, and can scale from a single script to a distributed fleet. Spider is suitable for building data pipelines for LLM and RAG, monitoring, data export, and AI browsing agents.

Spider asynchronously crawls websites, automatically discovering links and respecting crawl boundaries. It uses HTTP clients first and launches headless Chrome when JavaScript is needed. Pages are streamed back as soon as they are fetched, and users can subscribe to receive them. Configuration options include concurrency limit, crawl depth, delay, robots.txt respect, subdomain handling, user agent, and stealth mode. It can export content in Markdown, JSON, or WARC formats. It runs locally or via Spider Cloud, which provides proxy and auto-unblocking. All operations are performed through the Rust API or CLI.

  1. AI/LLM developers extracting web data from large volumes of pages to feed vector stores for RAG pipelines.
  2. SEO teams monitoring website changes, tracking rankings, or watching competitor updates.
  3. Price monitoring systems that regularly scrape product pages and compare prices.
  4. Researchers or analysts exporting web content as Markdown or JSON for processing or archiving.
  5. AI browsing agents driving headless Chrome to interact with dynamic websites.
  6. Teams needing high-concurrency crawling, scaling from a single script to a distributed cluster without code changes.

How do you install or deploy this agent?

To use as a Rust library, run cargo add spider in your project. For JavaScript rendering, enable the 'chrome' feature in Cargo.toml. Alternatively, install the CLI with cargo install spider_cli, use Node.js via npm i @spider-rs/spider-rs, or Python via pip install spider_rs.

How do you use this agent?

In Rust code, create a Website instance, set the target URL and configuration (such as concurrency and depth), then call crawl() or crawl_smart() to start crawling. Subscribe to receive streamed page data. Example:

use spider::{tokio, website::Website};

#[tokio::main]
async fn main() {
    let mut website = Website::new("https://example.com");
    let mut rx = website.subscribe(16);
    tokio::spawn(async move {
        while let Ok(page) = rx.recv().await {
            println!("{}  {}", page.status_code, page.get_url());
        }
    });
    website.crawl().await;
    website.unsubscribe();
}

What are this agent's strengths and limitations?

Pros
  • Concurrency-first design delivers high throughput and performance.
  • Streams pages as they are fetched, enabling real-time processing.
  • Built-in anti-bot measures, proxies, rate limiting, and retries.
  • Multi-language support: Rust, Node.js, Python, CLI.
  • Flexible deployment: local or managed via Spider Cloud.
Limitations
  • Primarily for Rust developers; other languages may have limited features.
  • JavaScript rendering requires headless Chrome, adding resource overhead.
  • For complex anti-bot scenarios, may rely on Spider Cloud's paid unblocking feature.
  • Documentation is extensive but some advanced configs require reading Rust docs.
  • Legal compliance for web scraping is the user's responsibility.

How does this agent compare with similar options?

Key facts side by side with the most closely related agents.

Agent Source review Form / cost Stars Updated Language Full support on
Spider - High-Performance Web Crawler and Scraper in Rust This agent 48 · Major gaps Library / SDKFreemium ★ 2.8k today Rust —
BrowserAct Skills: Real Browser Automation for AI Agents 48 · Major gaps CLIFreemium ★ 6.2k 1mo ago Python Codex · Claude Code
CamoFox Browser Server 72 · Some gaps Self-hosted serviceFree ★ 424 27d ago JavaScript Claude Code
Kuri 71 · Some gaps CLIFree ★ 366 10d ago Zig —

How does FollowAgents rate this agent?

FollowAgents source review · FARS-2.1
Major gaps
48/ 100 5-point scale 2.4 / 5
Trust 8/29
Reliability 8/14
Adaptability 10/18
Convention 10/18
Effectiveness 9/13
Verifiability 3/8
Why each dimension lost points
Trust8 / 29 · 1.4/5

Evidence shows: configuration options (with_limit, with_delay, with_respect_robots_txt) indicate some least privilege control; but no user confirmation mechanism (e.g., confirmation dialogs or approval flows). Data flow transparency: README describes page streaming and configuration, but does not detail data flow or processing details. Sensitive data handling: no explicit mention of handling sensitive data (e.g., API keys), but examples use API keys without secure storage advice. Dependency security: cargo-audit workflow exists, with explicit ignore of a known vulnerability (RUSTSEC-2026-0187), but only reachable via optional feature, no mitigation. External effects: crawler makes requests to external sites, but no explicit default robots.txt or rate limiting (though with_respect_robots_txt option exists). Rollback: no rollback mechanism mentioned. Source attribution: no explicit statement on content source or copyright.

Reliability8 / 14 · 2.9/5

Evidence shows: README and configuration examples are consistent, code structure clear, good self-consistency. Dependency availability: dependencies managed via crates.io, Cargo.lock likely present, but no offline or mirror solution. Failure messages: no detailed error handling or failure message examples.

Adaptability10 / 18 · 2.8/5

Evidence shows: README explicitly targets AI agents and LLMs, provides multiple use cases (RAG, monitoring, export). Capability boundaries: describes HTTP-first, on-demand JS rendering, but no explicit limits or boundaries. Trigger precision: no explicit trigger conditions or precise control. Environment fit: supports Rust, Node, Python, MCP, adaptable to multiple environments.

Convention10 / 18 · 2.8/5

Evidence shows: clear information architecture, README, docs links, examples directory. Install notes detailed, covering multiple languages. Naming stability: crate names and API naming consistent. Examples and FAQ: 50+ examples, but no FAQ. Known limitations: not explicitly listed. License: MIT, copyright notice clear. Versioning and changelog: version numbers present, but no changelog. Maintenance responsibility: SECURITY.md and contributing guide, but no explicit maintainers.

Effectiveness9 / 13 · 3.5/5

Evidence shows: output usability: supports multiple output formats (Markdown, JSON, WARC), page streaming. Marginal value: high-performance crawler and cloud service integration, unique value. Cost-benefit: local free, cloud has cost, but no detailed cost analysis.

Verifiability3 / 8 · 1.9/5

Evidence shows: performance claims in README lack benchmark data or test results. Cross-source verification: no third-party verification. Fact-inference separation: README mixes facts and inferences without clear distinction.

Risks and how to mitigate them
  • Not found in source: confirmation before actingTurn on (or add) a confirmation step before it acts, and try it in a sandbox or test environment before real data.
  • Not found in source: rollback or recovery pathBack up first, or work on a git branch or snapshot, so its changes can be undone.
  • No user confirmation mechanism, may automatically execute crawling operations.
  • Sensitive data handling (e.g., API keys) lacks secure storage advice.
  • Known dependency vulnerability (RUSTSEC-2026-0187) is ignored without mitigation.
  • Performance claims lack benchmark data support.
  • No changelog provided, version update information opaque.
Evidence confidence: Low Reviewed Aug 11, 2026 Reviewed revision 229e5cd43628 New commits since this review; the score may not cover them
See the full review method →

Recent releases

Latest entries from the project's GitHub Releases. Notes are quoted from upstream as written, not rewritten or tested by FollowAgents.

  1. v2.52.2 v2.52.2 — CLI authenticate for Spider Cloud
    Release notes excerpt
    Changes since vv1.7.5 - fix: concurrency/memory/panic audit hardening (v2.52.7) (#401) - chore(release): bump workspace to v2.52.6 - browser: per-crawl control map for optional chrome enhancements (#400) - chore(release): bump workspace to v2.52.5 - browser: genericize internal gateway topology/metrics in doc comments - browser: harden in-request gateway re-acquire (jitter, opt-out, timeouts) - security: fix cargo-audit failures (quick-xml DoS + lopdf) - chore(deps): bump actions/checkout from 4 to 7 (#399) - security: bump quinn-proto to 0.11.15 (RUSTSEC-2026-0185) …
    View on GitHub ↗
  2. v2.48.4
    Release notes excerpt
    New spider_mcp crate — MCP server for Spider. ```bash cargo install spider_mcp ``` Setup (Claude Code ~/.claude/settings.json or Claude Desktop config): ```json { "mcpServers": { "spider": { "command": "spider-mcp" } } } ``` Usage examples: ``` Scrape a page: "Fetch https://example.com as markdown" Crawl a site: "Crawl https://example.com up to 5 pages" Extract links: "Get all links from https://example.com" Transform HTML: "Convert this HTML to markdown: <h1>Hello</h1>" ``` Tools: spider_scrape · spider_crawl · spider_links · spider_transform
    View on GitHub ↗
  3. v2.48.2 v2.48.2 — Parallel Crawl Backends
    Release notes excerpt
    Race alternative browser engines alongside your primary crawl. Best HTML wins. ```rust use spider::configuration::{BackendEndpoint, BackendEngine, ParallelBackendsConfig}; let mut website = Website::new("https://example.com"); website.configuration.parallel_backends = Some(ParallelBackendsConfig { backends: vec![BackendEndpoint { engine: BackendEngine::LightPanda, endpoint: Some("ws://127.0.0.1:9222".to_string()), binary_path: None, protocol: None, }], ..Default::default() }); website.crawl().await; …
    View on GitHub ↗

FAQ

What is the difference between Spider and Spider Cloud?
Spider is the open-source crawling engine that runs locally; Spider Cloud is a managed service providing proxies, anti-bot unblocking, and infrastructure, available for a fee.
How do I enable JavaScript rendering?
Add the 'chrome' feature to your spider dependency and use the crawl_smart() method; Spider will automatically launch headless browsers for pages that need it.
What are the hardware or runtime requirements?
You need the Rust toolchain, and Chrome for JS rendering. High concurrency requires sufficient memory and network bandwidth.
Can I use Spider in commercial projects?
Yes, Spider is licensed under MIT, allowing commercial use. However, you must ensure compliance with website terms and laws.
View on GitHub ↗ Install ↓

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