Cloud Counter for AI Agents

Overview

Counter works by incrementing, decrementing, and resetting a cloud counter. It uses advanced algorithms to ensure the counter is updated accurately and returns the current value of the counter.

Live Test Cloud Counter for AI Agents Source →

The tool

Once your client is connected to the VerveContext server, this appears in its tool list as CloudCounterforAIAgents. 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": "CloudCounterforAIAgents",
  "arguments": {
    "id": "test_counter"
  }
}

You do not name the tool yourself; the model picks it. Asking about test_counter in the terms this source covers is enough for it to reach for CloudCounterforAIAgents 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
`id`Required	string	The ID of the counter (e.g., test_counter)

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": {
    "created": "2024-04-26T22:09:46.000Z",
    "id": "test_counter",
    "lastAction": "get",
    "lastRead": "2025-12-16T22:21:45.000Z",
    "lastUpdated": "2024-04-26T22:09:46.000Z",
    "numberOfDigits": 1,
    "ordinal": "zeroth",
    "value": 0,
    "words": "zero",
    "isEven": true,
    "isNegative": false,
    "isZero": true,
    "isPrime": false
  }
}

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
`created`	string	`2024-04-26T22:09:46.000Z`	ISO timestamp of when the counter was first created
`id`	string	`test_counter`	The identifier of the counter
`lastAction`	string	`get`	The most recent action performed on the counter (e.g., get, up, down, set)
`lastRead`	string	`2025-12-16T22:21:45.000Z`	ISO timestamp of when the counter was most recently queried
`lastUpdated`	string	`2024-04-26T22:09:46.000Z`	ISO timestamp of when the counter's value was last changed
`numberOfDigits`	number	`1`	The number of digits in the counter's current value, not counting a negative sign
`ordinal`	string	`zeroth`	The counter's current value spelled out as an ordinal word (e.g., "zeroth")
`value`	number	`0`	The counter's current numeric value
`words`	string	`zero`	The counter's current value spelled out in words (e.g., "zero")
`isEven`	boolean	`true`	Whether the counter value is even
`isNegative`	boolean	`false`	Whether the counter value is negative
`isZero`	boolean	`true`	Whether the counter value is zero
`isPrime`	boolean	`false`	Whether the counter value is a prime number

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 created: 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 2 credits each time the tool actually runs; a model that reasons about the tool without calling it costs nothing.

Use cases

Article View Counts: Increment a page tally each time a reader loads a blog post, returning the fresh total without querying a local database.
Feature Usage Quotas: To enforce monthly limits, SaaS backends increase a user action counter and check whether the total crosses allowed thresholds.
Live Score Tracking: Gaming servers adjust player points up or down during matches while fetching parity and formatted word representations.
Inventory Stock Adjustments: When shoppers complete checkout, decrement item tallies and inspect the remaining balance without maintaining dedicated database tables.

Other ways to use Cloud Counter for AI Agents

Set up Cloud Counter 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 →

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