Open Source Web Scraping: Why MIT License Matters

Most developers picking a scraping tool start with features: speed, output format, language support, price. The license usually gets a glance at best. You see “open source” on the landing page and move on.

That is a mistake. The license on your scraping dependency determines what you can build, how you can deploy it, and whether your company’s legal team will let you ship it. For scraping tools specifically, where the most common deployment pattern is running the tool as a backend service, the license choice has outsized consequences.

This post explains why Spider is MIT licensed, what that means in practice compared to AGPL and Apache 2.0, and why it should factor into your evaluation of any open source scraping tool.

How the major scraping tools are licensed

The four major open source scraping frameworks each made a different licensing decision:

These are not cosmetic differences. They define what you are legally allowed to do with the software in a production environment.

What each license actually requires

MIT (Spider)

The MIT license is two paragraphs long. It says: do whatever you want with this software. Include the copyright notice. That is the entire obligation.

You can:

• Use it in commercial products without disclosing your source code
• Modify it and keep your modifications private
• Deploy it as a service with no obligations to upstream
• Bundle it into proprietary software
• Sell products built on top of it

There is no copyleft. No patent clause. No requirement to contribute changes back. No distinction between internal use and public deployment.

Apache 2.0 (Crawl4AI, Crawlee)

Apache 2.0 is permissive and works well for most use cases. You can use it commercially, modify it, and distribute it. The two additions beyond MIT are:

1. Patent grant: Contributors grant you a license to any patents covering the code. This protects you from patent lawsuits by contributors.
2. Patent retaliation: If you sue a contributor for patent infringement related to the software, your patent license terminates.

For most teams, Apache 2.0 is fine. The patent clause is actually protective for users. Where it occasionally creates friction is during acquisition due diligence, where legal teams may flag the patent retaliation clause as a complication in the IP portfolio. This is uncommon but real.

AGPL 3.0 (Firecrawl)

AGPL is the GPL’s stricter sibling, designed specifically for the era of SaaS. Here is the critical provision: if you modify AGPL-licensed software and let users interact with it over a network, you must make your complete source code available under the AGPL.

This is not limited to the scraping library itself. The “corresponding source” requirement in AGPL Section 13 extends to the complete program. If your web service incorporates a modified version of an AGPL library, the entire service’s source code may need to be released.

The specific language from AGPL Section 13:

“If you modify the Program, your modified version must prominently offer all users interacting with it remotely through a computer network an opportunity to receive the Corresponding Source of your modified version.”

For a scraping tool, this is particularly relevant because scraping tools are almost always deployed as backend services.

BSL (Business Source License)

BSL is not used by any of the major scraping frameworks today, but it is worth mentioning because it has become common in adjacent infrastructure tools (databases, message queues). BSL restricts commercial use for a defined period (typically 3 to 4 years), after which the code converts to an open source license. It is effectively “source available” rather than open source.

The license comparison table

Real scenarios where AGPL creates problems

The abstract license comparison matters less than the concrete situations where license choice blocks or complicates real work. Here are four that come up repeatedly.

SaaS products with scraping features

You are building a SaaS product that includes web scraping as a feature. Maybe it is a competitive intelligence tool, a price monitoring service, or an AI assistant that can read web pages.

If you use an AGPL scraping library and modify it (fix a bug, add a feature, optimize performance), you must make your entire service’s source code available to your users under the AGPL. For a commercial SaaS company, this is a non-starter. Your proprietary business logic, your infrastructure code, your API layer, all of it may need to be disclosed.

With MIT, you modify the scraping library however you need, deploy your service, and your proprietary code stays proprietary.

Internal tools deployed as services

Many teams build internal scraping services: a microservice that other teams call to get web data. This is a standard architectural pattern.

Under AGPL, even an internal deployment where other employees interact with the service over the network can trigger the source disclosure requirement. The AGPL does not distinguish between public and internal network services. If users interact with the modified software over a network, the obligation applies.

Most companies’ legal teams will flag this and either block the tool entirely or require a time-consuming legal review.

Consulting and agency work

If you are a consulting firm or agency building scraping solutions for clients, AGPL creates a licensing chain reaction. The software you deliver to clients carries the AGPL obligation forward. Your client now has AGPL code in their stack, with all the disclosure requirements that entails. This is the kind of thing that surfaces during audits or acquisitions and creates expensive legal problems.

MIT-licensed dependencies pass through cleanly. The client gets the software with a simple copyright notice and no ongoing obligations.

Startups that might get acquired

During M&A due diligence, acquirers scan the target’s dependency tree for license risk. AGPL is consistently flagged as high-risk because the acquirer inherits the source disclosure obligations. This does not always kill deals, but it creates legal cost, delays timelines, and can affect valuation.

Apache 2.0’s patent retaliation clause occasionally gets flagged as well, though it is generally considered low-risk. MIT passes due diligence cleanly because there are no conditional obligations.

If you are a startup with any possibility of acquisition in the next five to ten years (which is most startups), the licenses in your dependency tree matter more than you think.

Why Spider chose MIT

Spider has been MIT licensed since the first commit. This was a deliberate decision, not a default.

The reasoning is straightforward: a web scraping tool is infrastructure. It collects data so you can do something useful with that data. The tool should not have opinions about what you build, how you deploy it, or whether you sell what you make. It should get out of the way.

Copyleft licenses make sense for end-user applications where the goal is to ensure the application itself stays free. A text editor, an operating system, a database. The GPL family was designed for that world.

We chose MIT because scraping is a data acquisition step in larger pipelines. Copyleft on this layer would propagate obligations into the application code above it, which is a poor trade-off for a library.

That said, AGPL exists for a legitimate reason. Firecrawl chose AGPL to prevent cloud providers from hosting their code as a competing service without contributing back. This is a real concern. A well-funded platform could fork an MIT-licensed project, add proprietary improvements, and offer it as a managed service. Spider mitigates this differently — through the managed API itself being the commercial product, not through license restrictions on the open source code.

Spider’s open source story

Spider’s Rust crate (spider-rs/spider) has been MIT-licensed since the first commit in 2023. The license has never changed and there are no plans to change it. If you are evaluating long-term dependency risk, that track record matters more than feature counts.

The feature flag system deserves a mention because it reflects the same philosophy as the license choice. You compile only what you need. If you are building a lightweight scraper for static sites, you do not carry the weight of Chrome integration, AI extraction, or proxy management. If you need everything, you enable everything. The tool adapts to your use case instead of forcing you into a one-size-fits-all binary.

Key capabilities of the OSS crate

The spider crate provides a complete crawling engine:

use spider::website::Website;
use spider::features::chrome_common::RequestInterceptConfiguration;

#[tokio::main]
async fn main() {
    let mut website = Website::new("https://example.com")
        .with_limit(100)
        .with_respect_robots_txt(true)
        .with_return_page_links(true)
        .build()
        .unwrap();

    website.crawl().await;

    for page in website.get_pages() {
        println!("{}: {} bytes", page.get_url(), page.get_html().len());
    }
}

The crate handles concurrent HTTP connections, sitemap discovery, robots.txt compliance, link extraction, CSS and JavaScript resource handling, Chrome integration for JavaScript-rendered pages, and content transformation to markdown. All of this is MIT licensed.

Contributions are welcome and encouraged. The project accepts pull requests, and the MIT license means your contributions carry no surprising obligations either. You can contribute a fix upstream and still use the same code in proprietary projects.

When to use the OSS crate vs. the cloud API

This is a question of operational complexity, not capability. The open source crate and the cloud API at spider.cloud use the same core engine. The difference is what you manage versus what the platform manages.

Use the OSS crate when:

• You want full control over the crawling infrastructure. You run your own servers, manage your own proxy rotation, and handle scaling yourself.
• You are building a product where the scraper is deeply embedded. The crate compiles into your Rust binary. There is no network hop, no API key, no external dependency at runtime.
• You are prototyping or experimenting. The crate runs locally with no account, no credits, and no network calls to external services.
• Compliance requirements demand on-premises processing. The data never leaves your infrastructure.
• You have Rust expertise on the team. The crate is idiomatic Rust with async/await, and feature flags let you customize the build precisely.

Use the cloud API when:

• You need managed proxy rotation. The API includes datacenter, residential, and mobile proxies with automatic escalation. Managing proxy providers yourself is expensive and time-consuming.
• You need anti-bot bypass at scale. Cloudflare, Akamai, Imperva, and Distil bypass is maintained by the platform and updated continuously.
• You do not want to manage infrastructure. No servers to provision, no scaling to handle, no monitoring to set up.
• You want native AI output. The API returns clean markdown with boilerplate stripped, or structured JSON from natural language prompts.
• You are working in Python, JavaScript, or another language. The API is language-agnostic. Official SDKs exist for Python, Node.js, Ruby, Go, C#, Java, and Rust.

The two options are not mutually exclusive. Some teams use the OSS crate for development and testing, then switch to the cloud API for production where proxy management and anti-bot handling are the platform’s problem.

Comparing the ecosystems

Each of the major open source scraping tools has built a different kind of ecosystem. Understanding these differences helps you pick the right tool for your situation.

Spider (MIT, Rust)

Spider’s open source crate is the same Rust engine that powers the managed API. The MIT license means you can embed it in proprietary products, fork it, or host it as a competing service. Performance details are on the API page.

Firecrawl (AGPL, TypeScript)

Firecrawl focuses on developer experience and AI-ready output. The TypeScript codebase is accessible to a large developer community, the API design is clean, and it has 30,000+ GitHub stars — significantly more community adoption than Spider’s crate. The managed service handles JavaScript rendering and returns markdown.

Firecrawl chose AGPL for a legitimate reason: preventing cloud providers from hosting their code as a competing service without contributing back. This is a real concern in the scraping space. If you use Firecrawl’s managed API, the AGPL does not affect you. But if you self-host or fork the code, you accept the source disclosure obligation. Firecrawl also offers commercial licenses for teams that need to avoid AGPL.

Crawl4AI (Apache 2.0, Python)

Crawl4AI is designed specifically for LLM workflows. The Python codebase integrates naturally with the Python ML ecosystem. The Apache 2.0 license is permissive and works well for commercial use.

The trade-off is performance. Python’s concurrency model (asyncio) handles I/O-bound work well but does not match Rust’s throughput for CPU-bound tasks like HTML parsing and content extraction at high volume. For moderate-scale LLM data collection, Crawl4AI is a solid choice. For high-throughput production pipelines, you may need to layer additional infrastructure on top.

Crawlee (Apache 2.0, JS/Python)

Crawlee (by Apify) provides a well-structured framework for building scrapers with built-in request queuing, storage, and error handling. The dual JavaScript/Python support covers a wide developer base. Apache 2.0 licensing is permissive.

The trade-off is that Crawlee is a framework, not a turnkey solution. You write the scraping logic. The framework handles the plumbing (queuing, retries, storage), but you still build and maintain the scrapers themselves. This gives maximum flexibility at the cost of more development time.

The business case for permissive licensing

Beyond individual scenarios, there is a structural argument for why scraping tools in particular should use permissive licenses.

Scraping is a data acquisition step in a larger pipeline. The value is not in the scraper. It is in what you do with the data: the AI model you train, the search index you build, the competitive analysis you deliver, the monitoring system you operate. A copyleft license on the scraping step threatens to encumber the entire pipeline.

This is different from, say, a database. If your database is AGPL (like MongoDB was before switching to SSPL), the copyleft applies to the database server itself. Your application talks to the database over a network protocol, and the license typically does not reach across that boundary. But a scraping library is linked directly into your application. It runs in your process. The copyleft boundary is much harder to draw.

For library code that gets embedded into other applications, MIT is the license that creates the least friction for the most users. That is why the Rust ecosystem overwhelmingly favors MIT and Apache 2.0 dual licensing, and why Spider chose MIT.

Getting started

Spider’s open source crate is on crates.io:

[dependencies]
spider = "2"

The cloud API uses pay-as-you-go pricing with no subscription. If you want to evaluate without a commitment, the crate runs locally with no account needed.

• GitHub: spider-rs/spider
• Crate: crates.io/crates/spider
• Cloud API: spider.cloud
• License: MIT