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People Data Labs MCP by usefulapi

Search companies

pdl_company_search
Read-only

Search the full PDL Company Dataset with an Elasticsearch query object OR a SQL string over the Company Schema (e.g. all SaaS companies with 50-200 employees in the US). Paginate with scroll_token. Each returned record costs 1 credit. API: POST /company/search.

Input Schema

NameRequiredDescriptionDefault
sqlNoSQL query string, e.g. SELECT * FROM company WHERE industry='computer software'.
fromNoLegacy offset (0-9999). Prefer scroll_token.
sizeNoNumber of records to return (1-100). Default 1.
queryNoElasticsearch query as a JSON string, e.g. {"query":{"term":{"industry":"computer software"}}} — pass the value of "query".
prettyNoPretty-print the JSON response.
titlecaseNoTitlecase the returned data.
scroll_tokenNoPagination token from a previous response.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  2. First observed

TDQS

A3.9/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations only declare readOnlyHint=true, so the description carries real added value: it discloses the credit cost per returned record ('Each returned record costs 1 credit') and the underlying endpoint (POST /company/search). It does not mention rate limits or per-request credit caps, but the cost model is meaningful operational context beyond the annotation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Four tight sentences that front-load the core action and example, then pagination, then cost, then endpoint. No filler, though the parenthetical example and trailing API line are slightly redundant with the schema.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a read-only search with full schema coverage and no output schema, the description covers query modes, pagination, and cost. It omits expected return shape and any guidance on maximum credits consumed per call, but nothing essential to invoking it correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so all seven parameters are already documented, including the scroll_token pagination pattern and the from/size offsets. The description reinforces the two query modes and pagination but adds no syntax or format detail the schema lacks, so baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (Search) and resource (full PDL Company Dataset), and the two supported query modes (Elasticsearch object or SQL string). Naming the 'Company Dataset' distinguishes it from siblings like pdl_person_search and pdl_job_posting_search without opening any schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains how to query (ES object OR SQL) and how to page (scroll_token), but never states when to choose this search tool over pdl_company_enrich or when SQL is preferable to the ES query path. Usage is implied rather than explicitly framed.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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