SiteCheck Company Records

US Census County Business Patterns by state: number

b2b_census_business_builder

Read-only

US Census County Business Patterns by state (latest year published, all legal forms): number of establishments, paid employees, first-quarter and annual payroll for a state FIPS code, for all industries or one NAICS code (2 to 6 digits). Official US Census Bureau data from its bulk state file. Aggregate counts only, no company names. Related tools on this server, for a different need: b2b_ny_business_entity when you need New York Department of State active corporations: searches; b2b_abr_australian_business_register when you need Australian Business Register, official register data: look. Price: $0.002 in USDC per successful call, paid with x402 (Base, Solana or Arc); failed calls are not charged.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "state": "<state>"
    },
    "name": "b2b_census_business_builder"
  }
}

Input Schema

Name	Required	Description	Default
`naics`	No	Optional NAICS code, 2 to 6 digits, e.g. 54 (professional services) or 541511
`state`	Yes	2-digit state FIPS code, e.g. 06 for California

Output Schema

Name	Required	Description	Default
`name`	No
`note`	No
`year`	No
`naics`	No
`state`	No
`source`	No
`checkedAt`	No
`employees`	No
`q1PayrollUsd`	No
`establishments`	No
`annualPayrollUsd`	No
`employeesNoiseFlag`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 23, 2026

TDQS

A4.4/5.0

Behavior5/5

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

Beyond readOnlyHint/openWorldHint, it discloses the data vintage (latest year published), legal-form coverage (all legal forms), the upstream source (official Census bulk state file), a critical output limitation (aggregate counts only, no company names), and the billing model ($0.002 USDC per successful call via x402 on Base/Solana/Arc, failures not charged). These are exactly the facts the annotations cannot convey.

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?

The core capability, scope, and limitation are front-loaded in the first two sentences, with pricing and sibling routing afterward. It is slightly overstuffed — the sibling-tool clause is verbose and the title keyword 'number' is never explained — but no sentence is pure filler.

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

Completeness5/5

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

An output schema exists, so return shape need not be described, and both parameters are fully documented in the schema. With vintage, aggregation granularity, source file, no-company-names caveat, and pricing all stated, an agent has everything needed to decide and invoke correctly.

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 coverage is 100%, so both parameters are already documented with examples (state FIPS '06', NAICS '54'/'541511'). The description restates the same facts — FIPS state code, NAICS 2–6 digits, all-industries default — without adding syntax, format, or fallback behavior beyond the schema. 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?

The description names the exact dataset (US Census County Business Patterns), the scope (by state FIPS, latest year published, all legal forms), and the measures returned (establishments, paid employees, Q1 and annual payroll). It also names two sibling tools with the distinct need each serves, so an agent can tell it apart 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 Guidelines4/5

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

It gives clear routing guidance by naming b2b_ny_business_entity and b2b_abr_australian_business_register as alternatives for different needs (state corporation records, Australian register). It also implicitly scopes use to aggregate statistics by state/NAICS, though it never states exclusions like 'do not use for company-level lookups' or whether non-US data is unsupported.

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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