Words-to-Numbers Conversion for AI Agents

The tool

Give enterprise agents written-number parsing through the same real-data layer, converting spelled-out phrases into numeric values per call.

Once your client is connected to the VerveContext MCP server, this appears in its tool list as Words-to-NumbersConversionforAIAgents. 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": "Words-to-NumbersConversionforAIAgents",
  "arguments": {
    "words": "seven thousand six hundred and twenty"
  }
}

What that looks like in a conversation

You don't name the tool — the model picks it. Asking about seven thousand six hundred and twenty in the terms this source covers is enough for it to reach for Words-to-NumbersConversionforAIAgents 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/mcp

Per-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.

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": {
    "number": "7620",
    "words": "seven thousand, six hundred twenty",
    "ordinal": "seven thousand, six hundred twentieth",
    "numberOfDigits_numeric": 4,
    "numberOfDigits_words": "four",
    "eachNumber": [
      "seven",
      "six",
      "two",
      "zero"
    ]
  }
}

Fields

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A model can produce something that looks like this answer from its training data, and be confidently out of date or simply wrong.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 number: 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.

Other ways to use Words-to-Numbers Conversion for AI Agents

Set up Words-to-Numbers Conversion 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