People Data Labs alternatives
The highest-scoring alternative to People Data Labs is Apollo at 64/100 on the AgentReady, against 50/100 for People Data Labs.
All scored in Company & Contact Data APIs.
What Apollo does that People Data Labs does not
Apollo passes clear canonical domain, mcp discoverable, authentication documented, limits / constraints documented, agent-compatible signup flow, cli available, mcp integration available, agent compatibility verified, and People Data Labs fails them. That is the whole of the gap between the two scores, so if none of those matter to your agent the ranking above overstates the difference.
Why people look for an alternative
People Data Labs fails clear canonical domain, mcp discoverable, structured api reference, openapi / spec quality, authentication documented, request examples provided, response examples provided, errors and status codes documented, limits / constraints documented, no mandatory sales call, agent-compatible signup flow, programmatic credential creation, cli available, mcp integration available, machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable, agent compatibility verified. Each one is a place an unattended run stops, which is usually what sends someone looking in the first place.
Where People Data Labs loses the points
| Pillar | People Data Labs | What it measures |
|---|---|---|
| Discover | 80 | Can an agent find it at all: sitemap, robots, structured data. |
| Understand | 23 | Is there a spec, an llms.txt, a machine-readable description. |
| Adopt | 50 | Signup, keys, SDKs, and whether a human has to be involved. |
| Operate | 47 | Rate-limit headers, errors, status, and behaviour under load. |
People Data Labs is weakest on understand at 23/100. Without a spec an agent has to guess at endpoints, and it guesses wrong. If that is the part your agent depends on, take the ranking above seriously; if it is not, People Data Labs may still be the right pick.
What an agent runs into with People Data Labs
These are the findings from the last audit on 2026-08-22. Each one is a place unattended software stops, which is the practical reason to look at the list above.
- Ship an MCP server so agents can call you as a tool.
- Publish MCP install instructions so agents can discover the server.
- Publish an OpenAPI spec so agents can generate a client.
- Flesh out the OpenAPI: paths, schemas, and descriptions.
- Document error responses as an enum in your OpenAPI.
- Let agents create API keys programmatically.
- Return X-RateLimit / Retry-After headers so agents pace themselves.
- Add request examples to your API reference.
What this category actually supports
Across the 7 products scored in Company & Contact Data APIs, enrich a person is offered by 29%, find b2b contacts is offered by 29%, enrich a company is offered by 14%, research a company is offered by 14%. Anything under half is a gap you should expect to fill yourself whichever one you pick.
An agent can get this list directly: resolve("alternative to People Data Labs") over the MCP server, or GET /v1/categories/data-enrichment.