Age Calculation for AI Agents
The tool
Give AI agents precise age math through the same real-data layer, turning any birth date into years, months and days per call.
Once your client is connected to the VerveContext MCP server, this appears in its tool list as AgeCalculationforAIAgents. It is read-only and open-world: it fetches, it never mutates anything on your side, so most clients will call it without asking you to confirm.
{
"name": "AgeCalculationforAIAgents",
"arguments": {
"dob": "1990-08-02"
}
}What that looks like in a conversation
You don't name the tool — the model picks it. Asking about 1990-08-02 in the terms this source covers is enough for it to reach for AgeCalculationforAIAgents on its own.
Connecting
One server URL covers every source in the catalog, including this one. Authorization is OAuth — the client opens a browser once and there is no key to paste into a config file.
{
"mcpServers": {
"vervecontext": {
"url": "https://api.vervecontext.com/v1/mcp"
}
}
}https://api.vervecontext.com/v1/mcpPer-client setup — Claude Desktop, Cursor, VS Code, ChatGPT — is on the MCP setup page.
Arguments
These are the properties on the tool's inputSchema, so a well-behaved client validates them before the call is made.
| Argument | Type | Example | Description |
|---|---|---|---|
dobRequired | string | 1990-08-02 | The date of birth to calculate the age from (format: YYYY-MM-DD) |
timezone | string | America/Chicago | IANA timezone used to interpret the date of birth and to determine "today" when computing the age |
What the model gets back
The result carries a structuredContent object matching the tool's declared outputSchema, so a client can read fields without parsing prose. status is "ok" on success and error is null; a null field means the value wasn't available for that input, not that the call failed.
{
"status": "ok",
"error": null,
"data": {
"dob": "1990-01-01",
"age_breakdown": {
"years": 35,
"months": 431,
"weeks": 1876,
"days": 13133,
"hours": 315208,
"minutes": 18912499,
"seconds": 1134749976
},
"age_words": {
"years": "thirty-five",
"ordinal": "thirty-fifth",
"full": "thirty-five years old",
"locale": "en-US"
},
"timezone": "America/Chicago",
"locale": "en-US",
"next_birthday": {
"months": 0,
"weeks": 2,
"days": 15,
"hours": 367,
"minutes": 22060,
"seconds": 1323623
},
"insights": {
"generation": "Millennial",
"zodiacSign": "Capricorn",
"chineseZodiac": "Horse",
"birthstone": "Garnet",
"dayOfWeekBorn": "Monday",
"isLeapYearBirth": false,
"milestones": {
"canVoteUS": true,
"canDrinkUS": true,
"canRentCarUS": true,
"seniorDiscount": false
}
}
}
}Fields
| Field | Type | Example | Description |
|---|---|---|---|
dob | string | Date of birth as provided in request (format: YYYY-MM-DD) | |
age_breakdown | object | Age expressed in years, months, weeks, days, hours, minutes, and seconds | |
└ age_breakdown.years | number | Person's age in complete years | |
└ age_breakdown.months | number | Total age in months | |
└ age_breakdown.weeks | number | Total age in weeks | |
└ age_breakdown.days | number | Total age in days | |
└ age_breakdown.hours | number | Total age in hours | |
└ age_breakdown.minutes | number | Total age in minutes | |
└ age_breakdown.seconds | number | Total age in seconds | |
age_words | object | Age expressed in words (e.g., thirty-five years old) | |
└ age_words.years | string | Age in written word form (e.g., thirty-five) | |
└ age_words.ordinal | string | Age in ordinal word form (e.g., thirty-fifth) | |
└ age_words.full | string | Age as complete phrase (e.g., thirty-five years old) | |
└ age_words.locale | string | Locale used for word generation (e.g., en-US) | |
timezone | string | Timezone associated with the calculation (e.g., America/Chicago) | |
locale | string | Locale code for the response (e.g., en-US) | |
next_birthday | object | Countdown to next birthday in months, weeks, days, hours, minutes, seconds | |
└ next_birthday.months | number | Months until next birthday | |
└ next_birthday.weeks | number | Weeks until next birthday | |
└ next_birthday.days | number | Days until next birthday | |
└ next_birthday.hours | number | Hours until next birthday | |
└ next_birthday.minutes | number | Minutes until next birthday | |
└ next_birthday.seconds | number | Seconds until next birthday | |
insights | object | ||
└ insights.generationPremium | string | Generational cohort (e.g., Millennial, Gen Z, Baby Boomer) | |
└ insights.zodiacSignPremium | string | Western zodiac sign based on birth date (e.g., Capricorn, Leo) | |
└ insights.chineseZodiacPremium | string | Chinese zodiac animal based on birth year (e.g., Dragon, Tiger) | |
└ insights.birthstonePremium | string | Traditional birthstone for birth month (e.g., Diamond, Ruby) | |
└ insights.dayOfWeekBornPremium | string | Day of the week person was born (e.g., Monday, Friday) | |
└ insights.isLeapYearBirthPremium | boolean | Whether the person was born in a leap year | |
└ insights.milestonesPremium | object | Legal milestones achieved (canVoteUS, canDrinkUS, canRentCarUS, seniorDiscount) | |
└ insights.milestones.canVoteUSPremium | boolean | Whether person is eligible to vote in United States elections | |
└ insights.milestones.canDrinkUSPremium | boolean | Whether person is legal age to drink alcohol in United States | |
└ insights.milestones.canRentCarUSPremium | boolean | Whether person meets age requirement to rent cars in United States | |
└ insights.milestones.seniorDiscountPremium | boolean | Whether person is eligible for senior citizen discounts |
Why ground on it
A model can produce something that looks like this answer from its training data, and be confidently out of date or simply wrong. This source returns the current value with a shape you can check, which is the difference between an answer you can cite and one you have to hedge.
Point an evaluation at locale: it is the field most worth pinning a claim to, and it is either present and current or absent — never plausibly invented.
Failure modes
Errors come back as tool errors with a sentence the model can act on, not a bare status code.
| Status | What it means |
|---|---|
400 / 422 | The arguments didn't validate. The message names the offending one. |
401 | The OAuth session is invalid or expired — reconnect the server. |
403 | Out of credits. Not a bad key — the month's allowance is spent. |
404 | This source isn't part of VerveContext. Check the catalog. |
429 | Brief rate limit. Retrying after a moment succeeds. |
Other ways to use Age Calculation for AI Agents
Set up Age Calculation for AI Agents on VerveContext, or reach the same source a different way. Your VerveContext account and credits work on all of them — one key, one balance.
Frequently asked questions
Do I have to tell the agent to use AgeCalculationforAIAgents?
No. The tool's name and description are in the model's context once the server is connected, so it selects the tool when the question calls for it. Naming it explicitly works too and is useful when you want to force the call.
Does connecting the server expose every tool at once?
Yes — one connection lists the whole VerveContext catalog. Clients with a tool budget can usually filter the list; the credit cost is per call, so an unused tool costs nothing.
What does a call cost?
1 credit each time the tool actually runs. A model that reasons about the tool without calling it costs nothing.
Is there a REST version of this?
Yes — the same source is available as a plain HTTPS endpoint on APIVerve, linked above. Same data, same credits, same account.