MCP server

Starwell: World Data & Statistics Official

dev.starwell/world-data-statistics

Checked 25 Oct 2026, 20:29 UTC · Connected to it and listed its tools

Statistics from 28 agencies: FRED, Eurostat, ECB, World Bank, OECD. Cited values, computed answers.

Website Source

At a glance

Type

MCP server

Publisher

starwell.dev (verified by the MCP Registry)

Status

Working at last check

Tools

11

Token cost

About 2,515 tokens per request

Sets up in

Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok

Last checked

25 Oct 2026, 20:29 UTC

Connect it to your agent

Add to CursorAdd to VS CodeVS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

claude mcp add --transport http world-data-statistics https://starwell.dev/api/starwell/mcp

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.world-data-statistics]
url = "https://starwell.dev/api/starwell/mcp"

Gemini CLI

{"mcpServers":{"world-data-statistics":{"httpUrl":"https://starwell.dev/api/starwell/mcp"}}}

Cursor

{"mcpServers":{"world-data-statistics":{"url":"https://starwell.dev/api/starwell/mcp"}}}

VS Code

{"servers":{"world-data-statistics":{"type":"http","url":"https://starwell.dev/api/starwell/mcp"}}}

Antigravity

agy mcp add world-data-statistics https://starwell.dev/api/starwell/mcp

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"world-data-statistics","server_url":"https://starwell.dev/api/starwell/mcp","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"world-data-statistics","server_url":"https://starwell.dev/api/starwell/mcp"}

Tools

• answer ~489 tokens
  The flagship: ask a natural-language question about the served official statistics. Returns a COMPUTED answer (real Python runs in a sandbox over the verified store, nothing is estimated by a model), the Plotly chart, the Python code, citations to the official tables, and a verification badge per se
• create_monitor ~218 tokens
  Create a monitor: when the store's refresh lands a new period or a revised value for the series, a series.updated webhook fires to your URL with the new value, verification status, and citation. Requires an API key (free with an account at /account); webhook must be https. Manage with list_monitors
• deep_analysis ~424 tokens
  The moat: a PLANNED multi-section report on a question. The engine designs 3-4 orthogonal analyses (trend, statistics, outliers, cross-series relationships), runs real Python for each in the sandbox over the verified store, and synthesizes one decision-ready report. Every number computed, every seri
• delete_monitor Deletes data · ~74 tokens
  Delete one of your monitors
• get_observations ~344 tokens
  Observation values for one series. Every value carries provenance (the exact source URL it came from, retrieval time, connector version) and the envelope carries the series verification status + citation. Defaults to the latest 60 points; use start/end (YYYY-MM-DD) or latest to control the window. P
• get_series ~180 tokens
  Full metadata for one series: indicator, unit, frequency, geography, coverage, its VERIFICATION STATUS (passing/stale/failing/unverified from golden-value + freshness checks against the live source), recent check records, and the citation to the official table.
• get_series_stats ~172 tokens
  Latest value, previous, all-time min/max, mean, and change vs the previous period and vs a year ago — computed over the verified store, with the citation attached. The cheap way to answer "what is it now and how has it moved" without a full analysis run.
• list_datasets ~115 tokens
  List the datasets (official releases/tables) available in one source, with coverage dates and links to the official table pages.
• list_monitors ~63 tokens
  Monitors on your API key, with delivery health (last fired, failures, active).
• list_sources ~94 tokens
  List the official statistical sources served by this data layer (e.g. Statistics Canada, FRED), with dataset/series counts, cadence notes, and terms links. Start here to see what exists.
• search_catalog ~342 tokens
  Find series across ALL sources in one call: case-insensitive search over series ids, indicator names, geographies, and dataset titles (e.g. "unemployment canada", "10-year treasury", "CPI"). Returns candidate series with units, coverage, verification status, and license, plus datasetMatches from the

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