Timezone Grounding Data for AI Agents

Overview

Timezone Lookup works by retrieving timezone data from a curated database and providing it in a structured format. The timezone database is updated regularly to ensure accurate and up-to-date information.

The tool

Once your client is connected to the VerveContext server, this appears in its tool list as TimezoneGroundingDataforAIAgents. It is read-only and open-world — it fetches and never mutates anything on your side — so most clients call it without asking you to confirm.

Tool call

{
  "name": "TimezoneGroundingDataforAIAgents",
  "arguments": {
    "city": "Harare"
  }
}

You do not name the tool yourself; the model picks it. Asking about Harare in the terms this source covers is enough for it to reach for TimezoneGroundingDataforAIAgents on its own — naming it explicitly also works, and is the way to force the call.

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"
    }
  }
}

Per-client setup — Claude, 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. Premium arguments are accepted on every plan but only take effect on plans that include them.

Argument	Type	Description
`city`Required	string	The city name for which you want to get the data (e.g., Harare)

What the model gets back

The result carries a structuredContent object matching the tool's declared outputSchema, so a client reads fields without parsing prose. status is "ok" and error is null on success; a null field means the value was not available for that input, not that the call failed.

Result

{
  "status": "ok",
  "error": null,
  "data": {
    "timezone": "Africa/Harare",
    "timezone_offset": 120,
    "date": "2025-12-17",
    "time": "00:30",
    "time24": "00:30:23",
    "time12": "12:30:23 AM",
    "day": "Wednesday",
    "month": "December",
    "year": "2025",
    "unix": "1765924223",
    "dst": false,
    "dst_start": "2025-12-17 00:30:23",
    "dst_end": "2025-12-17 00:30:23",
    "dst_name": "CAT"
  }
}

Response fields

Paths are relative to data. Premium fields are absent rather than zeroed on plans that do not include them, so check for presence instead of comparing to 0.

Field	Type	Example	Description
`timezone`	string	`Africa/Harare`	IANA timezone identifier for the city
`timezone_offset`	number	`120`	Timezone UTC offset in minutes from GMT
`date`	string	`2025-12-17`	Current date in YYYY-MM-DD format
`time`	string	`00:30`	Current time in HH:MM format
`time24`	string	`00:30:23`	Current time in 24-hour HH:MM:SS format
`time12`	string	`12:30:23 AM`	Current time in 12-hour AM/PM format
`day`Premium	string	`Wednesday`	Current day of week name
`month`Premium	string	`December`	Current month name
`year`Premium	string	`2025`	Current year as string value
`unix`Premium	string	`1765924223`	Current Unix timestamp in seconds
`dst`Premium	boolean	`false`	Whether daylight saving time is currently active
`dst_start`Premium	string	`2025-12-17 00:30:23`	DST start date and time in full format
`dst_end`Premium	string	`2025-12-17 00:30:23`	DST end date and time in full format
`dst_name`Premium	string	`CAT`	Daylight saving time zone abbreviation

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 in 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 timezone: 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 carrying a sentence the model can act on, not a bare status code. Error handling covers the full list.

Status	What it means
`400` / `422`	The arguments did not validate. The message names the offending one.
`401`	The OAuth session is invalid or expired — reconnect the server.
`403`	Blocked by a key restriction or an IP allow-list. Never a bad identity.
`404`	This source is not part of VerveContext. Check the catalog.
`429`	Out of credits, or a brief rate limit. The message tells them apart.

A call costs 1 credit each time the tool actually runs; a model that reasons about the tool without calling it costs nothing.

Use cases

World Clock: Use the Timezone Lookup API to get timezone data for a world clock. Use the data to display time zones, track time differences, and manage global operations
Travel Planning: Plan travel by using the Timezone Lookup API to get timezone data for destinations. Use the data to schedule flights, book accommodations, and manage itinerary
Meeting Scheduler: Schedule meetings by using the Timezone Lookup API to get timezone data for participants. Use the data to coordinate time zones, set meeting times, and avoid scheduling conflicts
Time Conversion: Convert time by using the Timezone Lookup API to get timezone data for time zones. Use the data to calculate time differences, synchronize clocks, and manage time zones

Other ways to use Timezone Grounding Data for AI Agents

Set up Timezone Grounding Data 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.

Call it as a REST APIOne HTTPS endpoint and an x-api-key header, with SDKs for Node, Python and .NET.APIVerve →Reference →

Give it to an AI agentConnect over MCP and your agent calls it as a native tool — Claude, Cursor, ChatGPT.VerveKit →Reference →

Use it in Google Sheets or ExcelA =VERVE() formula fills a column — no script, no export, recalculates in place.VerveSheets →Reference →