Oklahomaautoquotes

Register an insurance agency as a buyer

register_agency

For an AI working for a licensed insurance agency: register the agency to receive consented consumer requests in its states. Needs the agency name, the producer NPN (National Producer Number) and its state, the states it is appointed in, the licensed contact's name, email and mobile, and how leads should arrive (email, webhook, or pull by key). The licensed contact confirms by a link sent to their email; nothing is delivered before that. The first agencies in a state receive leads free for a founding period, then prepaid credits by card. Read /join for the terms.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`npn`	Yes	NPN (National Producer Number). Your NPN is on your licence and at nipr.com. Digits only.
`rail`	No	How leads arrive: email, an https webhook (HMAC-signed), or pull by key over MCP/REST	email
`states`	No	Two-letter states the agency is appointed in; defaults to npn_state
`website`	No
`npn_state`	Yes	Two-letter state that issued the licence
`sms_opt_in`	No	Optional. true only if the agency contact expressly agrees to this exact text: I agree to receive recurring operational text messages from CoverIntent by TheChattyAI about my agency account and consented lead deliveries. Message frequency varies. Message and data rates may apply. Reply HELP for help or STOP to cancel. Consent is not a condition of registering or buying.
`agency_name`	Yes
`webhook_url`	No
`contact_name`	Yes	The licensed contact, who confirms by email
`verify_token`	No	Optional: from POST /v1/verify/check after the contact enters the code texted to them
`contact_email`	Yes
`contact_phone`	Yes	US mobile

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

Changed1 schema field changedSep 7, 2026

addedInput schema / properties / sms_opt_in

Added value: +{
+  "default": false,
+  "description": "Optional. true only if the agency contact expressly agrees to this exact text: I agree to receive recurring operational text messages from CoverIntent by TheChattyAI about my agency account and consented lead deliveries. Message frequency varies. Message and data rates may apply. Reply HELP for help or STOP to cancel. Consent is not a condition of registering or buying.",
+  "type": "boolean"
+}

First observedSep 6, 2026

TDQS

A4.1/5.0

Behavior5/5

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

The description transparently discloses the confirmation via email link, that nothing is delivered before confirmation, and the billing model (free founding period, then prepaid credits). It also includes the full SMS opt-in consent text when applicable. These details go beyond the annotations.

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 description is longer than necessary but includes legally required SMS consent text and important process details (confirmation, billing, terms). It avoids redundancy and references external terms, keeping it efficient for the complexity.

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?

The description covers the full registration workflow, including prerequisites, confirmation, and billing, and notes that nothing is delivered before confirmation. It does not describe the output (no output schema exists), which is acceptable. Minor gaps like webhook_url specifics are present but not critical.

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 descriptions cover most parameters (npn, rail, states, npn_state, sms_opt_in, contact_name, verify_token, contact_phone), but agency_name, website, webhook_url, and contact_email lack schema descriptions. The tool description does not explicitly clarify webhook_url or website, leaving some ambiguity. Overall, coverage is partial and the description adds limited additional meaning.

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 clearly states the tool's purpose: registering an insurance agency to receive consented consumer requests in its states. It specifies the required inputs and the overall workflow. This is distinct and unambiguous.

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 provides implicit guidance on prerequisites (licensed agency, NPN, state appointments) and the confirmation process. However, it does not explicitly contrast with sibling tools like agency_status or check_eligibility, leaving the selection criteria somewhat inferred.

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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TDQS

A4/5.0

Disambiguation5/5

Each tool targets a distinct part of the workflow: eligibility, quoting, consent, agency registration, status, queue draining, and market data. There is no meaningful overlap, and descriptions clearly separate consumer-facing from agency-facing operations.

Naming Consistency4/5

Most tools follow a verb_noun pattern like check_eligibility, get_quotes, register_agency, and pull_requests. A few are noun phrases such as agency_status, market_data, and data_use_terms, but all are lowercase snake_case and predictable.

Tool Count5/5

Eight tools fit the server's scope well: the consumer quote/contact flow, agency lead handling, terms disclosure, and market data each have dedicated tools. None feel redundant, and the count is neither thin nor bloated.

Completeness4/5

The core lifecycle is well covered: check eligibility, get quotes, request agent contact, register an agency, check agency status, and pull requests. Minor gaps exist around explicit revocation/forget and agency updating, though these are hinted at in descriptions.

Resources

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