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Clearbit vs People Data Labs

Clearbit scores higher on the AgentReady, 53/100 against 50/100. They differ on 15 of the 41 signals. Which ones decides whether an agent can adopt them without a person watching.

What each one is

Clearbit. Clearbit is a B2B data provider that gathers public data from the web, proprietary data, and uses LLMs to convert unstructured information into precise and standardized data sets.

People Data Labs. Talent sourcing platform that builds workforce data, so you don't have to.

Where Clearbit is ahead

Clearbit passes clear canonical domain and mcp discoverable, and People Data Labs does not. That is discover, whether an agent can find the product at all without being told it exists.

It also holds understand: authentication documented. People Data Labs misses it.

And on adopt, agent-compatible signup flow, cli available and mcp integration available. People Data Labs misses those.

Finally, on operate, agent compatibility verified. People Data Labs misses it.

Where People Data Labs is ahead

People Data Labs passes llms.txt published and llms-full.txt / full agent docs, and Clearbit does not. That is discover, whether an agent can find the product at all without being told it exists.

It also holds understand: pricing understandable. Clearbit misses it.

And on adopt, self-service signup, free trial or free allowance, fast time to first request and copyable quickstart. Clearbit misses those.

Finally, on operate, structured, predictable output. Clearbit misses it.

What neither does

Both fail structured api reference, openapi / spec quality, request examples provided, response examples provided, errors and status codes documented, limits / constraints documented, no mandatory sales call, programmatic credential creation, machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable. 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 is whether an agent can find the product at all without being told it exists. Clearbit leads 87 to 80. Clearbit misses llms.txt published, llms-full.txt / full agent docs; People Data Labs misses clear canonical domain, mcp discoverable.

Understand. Both sit at 23/100 here. Clearbit misses structured api reference, openapi / spec quality, pricing understandable, request examples provided, response examples provided, errors and status codes documented, limits / constraints documented; People Data Labs misses structured api reference, openapi / spec quality, authentication documented, request examples provided, response examples provided, errors and status codes documented, limits / constraints documented.

Adopt. Both sit at 50/100 here. Clearbit misses self-service signup, no mandatory sales call, programmatic credential creation, free trial or free allowance, fast time to first request, copyable quickstart; People Data Labs misses no mandatory sales call, agent-compatible signup flow, programmatic credential creation, cli available, mcp integration available.

Operate. Clearbit leads 53 to 47. Clearbit misses structured, predictable output, machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable; People Data Labs misses machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable, agent compatibility verified.

Pricing

Clearbit does not publish a machine-readable starting price. People Data Labs does not publish one and has a free tier.

Signal by signal

Which to pick

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

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