Name Parsing for AI Agents

Overview

Human Name Parser works by analyzing the human name provided and parsing it into its components. It uses advanced algorithms to parse the human name into its components and returns the parsed components.

Live Test Name Parsing for AI Agents Source →

The tool

Once your client is connected to the VerveContext server, this appears in its tool list as NameParsingforAIAgents. 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": "NameParsingforAIAgents",
  "arguments": {
    "name": "MR. MARTINO PETROS DE FLORENCE (TINO) Jr."
  }
}

You do not name the tool yourself; the model picks it. Asking about MR. MARTINO PETROS DE FLORENCE (TINO) Jr. in the terms this source covers is enough for it to reach for NameParsingforAIAgents 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
`name`Required	string	The human name to parse

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": {
    "name": "MR. MARTINO PETROS DE FLORENCE (TINO) Jr.",
    "parsed": {
      "title": "Mr.",
      "first": "Martino",
      "middle": "Petros",
      "last": "de Florence",
      "nick": "Tino",
      "suffix": "Jr."
    },
    "initials": "MPF",
    "formalName": "Mr. de Florence, Martino P. Jr."
  }
}

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
`name`	string	`MR. MARTINO PETROS DE FLORENCE (TINO) Jr.`	The original human name provided for parsing
`parsed`	object	`{…}`	The name split into its parts
`parsed.title`	string	`Mr.`	Title or prefix extracted from the name (e.g., Mr., Mrs.)
`parsed.first`	string	`Martino`	First name component of the parsed name
`parsed.middle`	string	`Petros`	Middle name component of the parsed name
`parsed.last`	string	`de Florence`	Last name or surname component of the parsed name
`parsed.nick`	string	`Tino`	Nickname or preferred name extracted from parentheses
`parsed.suffix`	string	`Jr.`	Suffix or post-nominal letters (e.g., Jr., Sr., PhD)
`initials`	string	`MPF`	Initials derived from first, middle, and last name
`formalName`Premium	string	`Mr. de Florence, Martino P. Jr.`	Formally formatted name (Title Last, First M. Suffix)

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 initials: 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

Checkout Registration Form: When customers submit a single name field at checkout, separate their first and last names to populate billing and shipping records correctly.
CRM Contact Import: Sales teams importing raw lead lists parse contact strings into prefixes, given names, surnames, and post-nominals before syncing with databases.
Email Personalization Tokens: To address recipients casually in campaign greetings, extract nicknames or given names instead of sending unformatted full string headers.
User Avatar Generation: Feed derived initials into account dashboards to render placeholder profile graphics whenever a user signs up without uploading an avatar.

Other ways to use Name Parsing for AI Agents

Set up Name Parsing 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 →