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Kernel vs Oxylabs

Kernel scores higher on the AgentReady, 89/100 against 43/100. They differ on 19 of the 41 signals. Which ones decides whether an agent can adopt them without a person watching.

What each one is

Kernel. Kernel provides crazy fast, open source browser infrastructure for AI agents to access the internet.

Oxylabs. Oxylabs provides proxy services and web scraping solutions for accessing public web data fast and at scale.

Where Kernel is ahead

Kernel passes machine-readable metadata, and Oxylabs does not. That is discover, whether an agent can find the product at all without being told it exists.

It also holds understand: structured api reference, openapi / spec quality, pricing understandable, request examples provided, response examples provided, errors and status codes documented and limits / constraints documented. Oxylabs misses those.

And on adopt, self-service signup, programmatic credential creation, free trial or free allowance and cli available. Oxylabs misses those.

Finally, on operate, structured, predictable output, machine-readable errors, retry behavior documented, rate-limit behavior predictable, observable execution and agent compatibility verified. Oxylabs misses those.

Where Oxylabs is ahead

Oxylabs passes copyable quickstart, and Kernel does not. That is adopt, whether an agent can get a key and make its first successful call without a human in the loop.

What neither does

Both fail authentication documented, no mandatory sales call, agent-compatible signup flow, fast time to first request, idempotency support. If your agent needs any of those, you will be building it yourself either way.

Score, pillar by pillar

The AgentReady splits into four pillars, scored separately, because a product can be easy to find and still impossible to adopt.

Discover. Kernel leads 100 to 93. Kernel misses nothing; Oxylabs misses machine-readable metadata.

Understand is whether an agent can read the docs and work out how the API behaves before calling it. Kernel leads 92 to 15. Kernel misses authentication documented; Oxylabs misses structured api reference, openapi / spec quality, authentication documented, pricing understandable, request examples provided, response examples provided, errors and status codes documented, limits / constraints documented.

Adopt. Kernel leads 71 to 40. Kernel misses no mandatory sales call, agent-compatible signup flow, fast time to first request, copyable quickstart; Oxylabs misses self-service signup, no mandatory sales call, agent-compatible signup flow, programmatic credential creation, free trial or free allowance, fast time to first request, cli available.

Operate. Kernel leads 94 to 24. Kernel misses idempotency support; Oxylabs misses structured, predictable output, machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable, observable execution, agent compatibility verified.

Pricing

Kernel starts at $0/mo and has a free tier. Oxylabs does not publish one.

Signal by signal

Which to pick

Kernel clears more of the signals an agent needs, so it is the safer default for unattended use. Full profiles: Kernel and Oxylabs. Alternatives to each: Kernel, Oxylabs.

An agent can fetch this as data: POST /v1/compare {"slugs": ["kernel", "oxylabs"]}