Trade Balance Grounding Data for AI Agents

Overview

Trade Balance sources data from FRED (Federal Reserve Economic Data) using the Census Bureau FT-900 Balance of Payments series, providing seasonally adjusted monthly exports, imports, and the trade balance in millions of US dollars, with history back to 1992.

Live Test Trade Balance Grounding Data for AI Agents Source →

The tool

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

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
`date`Optional	string	Optional date in YYYY-MM format for historical lookup. Omit for current data. date

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": {
    "yearMonth": "2026-07",
    "year": 2026,
    "month": 7,
    "exports": 310723,
    "imports": 399299,
    "balance": -88576,
    "unit": "millions_usd",
    "exportsFormatted": "$310.72 billion",
    "importsFormatted": "$399.30 billion",
    "balanceFormatted": "-$88.58 billion",
    "tradeStatus": "deficit",
    "updatedAt": "2026-09-16T16:03:38.440Z"
  }
}

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
`yearMonth`	string	`2026-07`	Year and month in YYYY-MM format for the trade data
`year`	number	`2026`	The calendar year for the trade balance data
`month`	number	`7`	The month number (1-12) for trade balance data
`exports`	number	`310723`	US exports of goods and services for the month, in millions of USD (BOP basis, seasonally adjusted)
`imports`	number	`399299`	US imports of goods and services for the month, in millions of USD (BOP basis, seasonally adjusted)
`balance`	number	`-88576`	Trade balance (exports minus imports) for the month, in millions of USD. Negative means a trade deficit
`unit`	string	`millions_usd`	Unit for the exports, imports, and balance figures (millions_usd)
`exportsFormatted`Premium	string	`$310.72 billion`	Human-readable exports figure (e.g., $265.20 billion)
`importsFormatted`Premium	string	`$399.30 billion`	Human-readable imports figure (e.g., $340.40 billion)
`balanceFormatted`Premium	string	`-$88.58 billion`	Human-readable trade balance figure (e.g., -$75.20 billion)
`tradeStatus`	string	`deficit`	Whether the month was a trade deficit or surplus
`updatedAt`	string	`2026-09-16T16:03:38.440Z`	ISO 8601 timestamp when the trade data was last updated

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 yearMonth: 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

Economic Analysis: Track US trade patterns for economic research
Policy Research: Analyze trade data for policy research and analysis
Business Intelligence: Factor trade trends into business planning

Other ways to use Trade Balance Grounding Data for AI Agents

Set up Trade Balance 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 →

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