Starwell: World Data & Statistics

dev.starwell由 starwell.dev 發布官方發布者v0.2.2更新於 Oct 27, 2026

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

已驗證Streamable HTTP可網頁執行金融知識與記憶資料與分析

概覽

AI 產生的概覽

讓助理取得來自 28 個機構(FRED、Eurostat、世界銀行、OECD 等)可引用的官方統計資料,並提供計算答案、圖表與序列監控。

可以做什麼
  • 瀏覽資料來源與資料集,並跨所有機構搜尋序列
  • 讀取序列中繼資料、驗證狀態、附來源出處的觀測值與快速統計
  • 以自然語言提問,取得含圖表、程式碼與引用的計算答案
  • 針對一個問題產出多章節的深度分析報告
  • 建立、列出與刪除在序列更新時觸發的 webhook 監控
適用情境
適合助理需要可信、可引用官方表格的總體經濟或勞動統計資料,而非模型估算數字的情況;也適合需要在新週期或修訂資料發布時收到通知的情境。
執行需求
遠端 Streamable HTTP 端點,或以 npx 執行 starwell-mcp npm 套件(需 Node.js)。資料讀取不需憑證;answer、deep_analysis 與監控工具需要免費的 STARWELL_API_KEY。監控需要 https webhook 網址。需能連線至 Starwell 服務。
安裝前請注意
API 金鑰是作為 Bearer 憑證傳送的機密,請勿寫入共用設定。監控會把序列更新推送到你提供的 webhook 網址,該網址及其接收端會看到相關資料。建立與刪除監控會變更帳戶狀態。查詢與問題會傳送到 Starwell 服務。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Starwell: World Data & Statistics,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。

交給代理程式安裝

把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式,或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南,先向你展示發布者、端點和登入方式,經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。

閱讀 https://sourceweft.com/mcp/dev.starwell%2Fworld-data-statistics/install.md,並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前,先告訴我它的發布者、端點和登入方式,等我確認。不要把 API 金鑰寫進命令或我會提交的檔案;問我金鑰應從哪裡取得。

檢視代理程式所依據的安裝指南

其他 MCP 客戶端

把它新增到你客戶端的 mcpServers 設定中。

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

README

starwell-mcp

Starwell is the verified data layer for AI: official statistics from Statistics Canada, FRED, the U.S. Bureau of Labor Statistics, the World Bank, SEC EDGAR, the U.S. Treasury, the European Central Bank, the UK Office for National Statistics, INSEE (France), the Australian Bureau of Statistics, the OECD, Eurostat, INE (Spain), the Czech National Bank, ILOSTAT, Statistics Netherlands, the CDC, Statistics Sweden, Statistics Norway, Statistics Finland, Statistics Austria, the Department of Statistics Malaysia, the U.S. Bureau of Economic Analysis, the Central Statistics Office of Ireland, Statistics Denmark, Statistics Poland, Statistics Estonia, Statistics Iceland, and the U.S. Bureau of Transportation Statistics, served as MCP tools. Every observation carries provenance, every series carries a verification status backed by golden-value checks against the live source, and the answer tool returns computed results cited to the official table.

This package is a thin stdio bridge to the Starwell remote MCP server. The tool surface always matches the server, so new sources and tools appear without a package update.

Tools (12): search_catalog, list_sources, list_datasets, get_series, get_series_stats, get_observations, factory_status, answer, deep_analysis, create_monitor, list_monitors, delete_monitor. Reads are open; answer, deep_analysis, and the monitor tools need a free API key (STARWELL_API_KEY).

Install per client

Remote-capable clients can skip this package and add the URL directly: https://starwell.dev/api/starwell/mcp (Streamable HTTP).

Claude Code

sh
claude mcp add --transport http starwell https://starwell.dev/api/starwell/mcp# or via stdio:claude mcp add starwell -- npx -y starwell-mcp

Claude Desktop / claude.ai

Settings, Connectors, Add custom connector, URL https://starwell.dev/api/starwell/mcp. On plans without remote connectors, use the desktop config:

json
{  "mcpServers": {    "starwell": { "command": "npx", "args": ["-y", "starwell-mcp"] }  }}

Cursor

.cursor/mcp.json:

json
{  "mcpServers": {    "starwell": { "command": "npx", "args": ["-y", "starwell-mcp"] }  }}

OpenAI Codex CLI

~/.codex/config.toml:

toml
[mcp_servers.starwell]command = "npx"args = ["-y", "starwell-mcp"]

Gemini CLI

~/.gemini/settings.json:

json
{  "mcpServers": {    "starwell": { "httpUrl": "https://starwell.dev/api/starwell/mcp" }  }}

ChatGPT (developer mode)

Settings, Apps, enable developer mode, add connector with the remote URL above.

Configuration

  • STARWELL_MCP_URL: override the endpoint (staging, self-hosted).
  • STARWELL_API_KEY: Bearer key from https://starwell.dev/account (free). Data reads work without one; answer, deep_analysis, and monitors require it.

Data licensing

Only openly licensed official sources are served, each with its license and attribution in every response. The set covers U.S. federal statistical works (public domain), the Statistics Canada Open Licence, World Bank CC BY-4.0, and the respective open licences of the ECB, OECD, ONS, INSEE, and ABS. This product uses the FRED API but is not endorsed or certified by the Federal Reserve Bank of St. Louis.

Docs: https://starwell.dev/docs


This repository is the source of the starwell-mcp npm package. It is generated from Starwell's main repository, so pull requests here may be applied upstream by hand — but issues are read and very welcome.

來源:README.md,提交 fb582c6

工具

11

list_sources

List data sources

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.

無需輸入參數。

search_catalog

Search the series catalog

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 wider dataset index — datasets whose series can be requested by source-native id and are fetched from the official source on first call. The fastest path from a question to the exact series id to fetch or pin in the answer tool.

輸入參數limitquery必填offsetsource

list_datasets

List datasets in a source

List the datasets (official releases/tables) available in one source, with coverage dates and links to the official table pages.

輸入參數source必填

get_series

Get series metadata + verification

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.

輸入參數source必填seriesId必填

get_observations

Get observations (with provenance)

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. Pass asOf for a point-in-time read: the values as Starwell's store held them on that date, before any later revision (available from the series' first ingest forward).

輸入參數endasOfstartlatestsource必填seriesId必填

get_series_stats

Summary statistics for a series

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.

輸入參數source必填seriesId必填

create_monitor

Watch a series (webhook on movement)

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 / delete_monitor.

輸入參數source必填seriesId必填webhookUrl必填

list_monitors

List your monitors

Monitors on your API key, with delivery health (last fired, failures, active).

無需輸入參數。

delete_monitor

Delete one of your monitors

輸入參數id必填

answer

Answer a question from verified data

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 series. CROSS-SOURCE: one question may join series from DIFFERENT agencies, e.g. unemployment from the US BLS, Statistics Canada and the UK ONS in a single call, for correlations, ratios, and like-for-like comparison. How many series one question may join is set by the caller's plan; asking for more returns a series_limit error naming that cap. Returns a refusal when no served series can answer. Takes 10-40 seconds. Requires a free API key (create at /account on the Starwell host; pass Authorization: Bearer dlk_... or set STARWELL_API_KEY on the starwell-mcp bridge). Keyless calls return key_required.

輸入參數endsharestartseriesquestion必填

deep_analysis

Deep multi-angle analysis from verified data

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 series cited and verification-badged. Sections can join series from DIFFERENT agencies in one report, up to the caller's plan width; over it, the call returns a series_limit error naming that cap. Slower than answer (60-180 seconds), so use it for "analyze", "break down", "give me a full picture" asks; use the answer tool for a single direct question. Requires a free API key (create at /account on the Starwell host; pass Authorization: Bearer dlk_... or set STARWELL_API_KEY on the starwell-mcp bridge). Keyless calls return key_required.

輸入參數endstartseriesquestion必填

版本歷史

1
  1. v0.2.2最新Sep 16, 2026

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