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us_entity

US state business-entity (Secretary of State) lookup across NY, CO, CT, OR, TX and VA official open-data registries in one call, by name (all 6 states) or state+id. Entity name, state id, status/good standing, type, formation date, jurisdiction of formation, address, registered agent, CT principals, red flags (inactive, new <6 months, same name in several states). Example: {name:"Etsy Inc"} or {state:"CO",id:"20211537536"}. $0.25 USDC.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "us_entity"
  }
}

Input Schema

NameRequiredDescriptionDefault
qNo
idNo
nameNo
limitNo
stateNo
numberNo
companyNo
entity_idNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations supplied, the description carries the load and does disclose the source registries, the derived red-flag logic (inactive, formed <6 months, same name across states), and the $0.25 USDC cost. It omits payment/auth mechanics and any rate or result-cap behavior, which an agent would want to know before calling a paid 8-parameter endpoint.

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?

Front-loaded with coverage and access pattern, then the return payload, then two examples and the price — a sensible ordering with almost no filler. The listing of returned fields is dense but each item is informational rather than padding.

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

Completeness3/5

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

With no output schema and no annotations, the description compensates well on return content and cost, which is the main burden here. It falls short on the parameter surface, leaving five of eight inputs undefined, so an agent cannot be fully confident it will build a valid request.

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

Parameters2/5

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

Schema description coverage is 0% across 8 parameters, so the description must explain them, but it only accounts for name, state, and id. It is silent on q, limit, number, company, and entity_id, and never clarifies whether the overlapping name/company and id/entity_id/number fields are aliases or different lookups — a real risk of malformed calls.

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 concrete verb and resource — Secretary of State business-entity lookup — and pins the scope to six named state registries in a single call. It also enumerates the returned fields, so an agent can distinguish it from the SEC-oriented siblings (us_sec, us_sec_full) and the generic company/kyb tools without opening a 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?

Gives the two supported invocation modes explicitly (by name across all 6 states, or by state+id) plus a worked example for each. It never names a when-not condition or a preferred alternative for cases outside those six states, leaving the agent to infer which sibling to fall back on.

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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