Address Parsing for AI Agents

Overview

Street Address Parser works by analyzing the US street address provided and parsing the components. It uses advanced algorithms to parse the street address and returns the parsed components such as street number, street name, city, state, and more.

The tool

Once your client is connected to the VerveContext server, this appears in its tool list as AddressParsingforAIAgents. 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": "AddressParsingforAIAgents",
  "arguments": {
    "address": "1600 Amphitheatre Parkway, Mountain View, CA 90210"
  }
}

You do not name the tool yourself; the model picks it. Asking about 1600 Amphitheatre Parkway, Mountain View, CA 90210 in the terms this source covers is enough for it to reach for AddressParsingforAIAgents 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
`address`Required	string	The street address 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": {
    "address": "1600 Amphitheatre Parkway, Mountain View, CA 90210",
    "parsed": {
      "streetNumber": "1600",
      "streetType": "Pkwy",
      "streetAddress": "Amphitheatre",
      "cityName": "Mountain View",
      "stateName": "CA",
      "zipCode": "90210"
    }
  }
}

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
`address`	string	`1600 Amphitheatre Parkway, Mountain View, CA 90210`	The original street address provided for parsing
`parsed`	object	`{…}`
`parsed.streetNumber`	string	`1600`	House or building number from the address
`parsed.streetType`	string	`Pkwy`	Abbreviated street type like Pkwy, St, Ave
`parsed.streetAddress`	string	`Amphitheatre`	The name of the street parsed from address
`parsed.cityName`	string	`Mountain View`	City name extracted from the address
`parsed.stateName`	string	`CA`	State abbreviation parsed from address
`parsed.zipCode`	string	`90210`	Postal code extracted from the address

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 parsed.streetNumber: 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

Address Verification: Use the Street Address Parser API to parse street addresses for address verification. Use the data to validate addresses, correct errors, and enhance data quality
Geocoding: Use the data to convert addresses to geographic coordinates, map locations, and enhance spatial analysis.
Location Intelligence: Use the data parse street addresses for location intelligence. Use the data to analyze addresses, identify trends, and make informed decisions
Data Enrichment: Parse street addresses by using the Street Address Parser API for data enrichment. Use the data to enhance address information, improve data quality, and enrich datasets

Other ways to use Address Parsing for AI Agents

Set up Address 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 →

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