Global Market Grounding Data

Overview

Global Stock Market provides monthly share price index data for major economies worldwide. The index is normalized to 2015=100, making it easy to compare relative market performance across countries. Data spans from 2000 to present for most countries. Use this for economic research, country comparison, and global market analysis.

Live Test Global Market Grounding Data Source →

The tool

Once your client is connected to the VerveContext server, this appears in its tool list as GlobalMarketGroundingData. 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.

{
  "name": "GlobalMarketGroundingData",
  "arguments": {
    "country": "DE"
  }
}

You do not name the tool yourself; the model picks it. Asking about DE in the terms this source covers is enough for it to reach for GlobalMarketGroundingData 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"
    }
  }
}

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.

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.

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{
  "status": "ok",
  "error": null,
  "data": {
    "country": "DE",
    "countryName": "Germany",
    "baseline": "2015=100",
    "year": 2023,
    "month": 6,
    "value": 154.28,
    "date": "2023-06-01"
  }
}

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.

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 countryName: 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.

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

Country Comparison

Compare stock market performance between countries like Germany vs France over the past decade

Economic Research

Analyze global market trends and correlations between national economies

Investment Analysis

Evaluate which country markets have outperformed or underperformed relative to 2015 baseline

Market Dashboards

Build global market overview dashboards showing performance across regions

Other ways to use Global Market Grounding Data

Set up Global Market Grounding Data on VerveContext, or reach the same source a different way. Your VerveContext account and credits work on all of them — one key, one balance.

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