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Clay vs People Data Labs

People Data Labs scores higher on the AgentReady, 50/100 against 47/100. They differ on 14 of the 41 signals. Which ones decides whether an agent can adopt them without a person watching.

What each one is

Clay. Clay is a go-to-market data platform that provides data infrastructure, AI agents, orchestration, and execution tools for sales and marketing teams.

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

Where Clay is ahead

Clay 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 adopt: no mandatory sales call, agent-compatible signup flow, cli available and mcp integration available. People Data Labs misses those.

Where People Data Labs is ahead

People Data Labs passes clear product positioning, llms.txt published and llms-full.txt / full agent docs, and Clay 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. Clay misses it.

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

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

What neither does

Both fail structured api reference, openapi / spec quality, authentication documented, request examples provided, response examples provided, errors and status codes documented, limits / constraints documented, programmatic credential creation, machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable, agent compatibility verified. 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. People Data Labs leads 80 to 73. Clay misses clear product positioning, llms.txt published, llms-full.txt / full agent docs; People Data Labs misses clear canonical domain, mcp discoverable.

Understand. People Data Labs leads 23 to 15. Clay 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; 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 is whether an agent can get a key and make its first successful call without a human in the loop. Clay leads 65 to 50. Clay misses self-service signup, programmatic credential creation, free trial or free allowance, fast time to first request; People Data Labs misses no mandatory sales call, agent-compatible signup flow, programmatic credential creation, cli available, mcp integration available.

Operate. People Data Labs leads 47 to 35. Clay misses structured, predictable output, machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable, agent compatibility verified; People Data Labs misses machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable, agent compatibility verified.

Pricing

Clay 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: Clay and People Data Labs. Alternatives to each: Clay, People Data Labs.

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