Starwell: World Data & Statistics

dev.starwell由 starwell.dev 发布官方发布者v0.2.2更新于 Oct 27, 2026

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

已验证Streamable HTTP可网页运行金融知识与记忆数据与分析

概览

AI 生成的概览

让助手获取来自 28 家机构(FRED、Eurostat、世界银行、OECD 等)的可引用官方统计数据,并提供计算答案、图表和序列监控。

可以做什么
  • 浏览数据来源与数据集,并跨所有机构检索序列
  • 读取序列元数据、校验状态、带来源出处的观测值和快速统计
  • 用自然语言提问,获得含图表、代码和引用的计算答案
  • 针对一个问题生成多章节的深度分析报告
  • 创建、列出和删除在序列更新时触发的 webhook 监控
适用场景
当助手需要可信、可引用官方表格的宏观经济或劳动力统计数据,而不是模型估算的数字时适用;也适合需要在新周期或修订数据发布时收到提醒的场景。
运行要求
远程 Streamable HTTP 端点,或通过 npx 运行 starwell-mcp npm 包(需 Node.js)。数据读取无需凭据;answer、deep_analysis 和监控工具需要免费的 STARWELL_API_KEY。监控需要 https webhook 地址。需能访问 Starwell 服务。
安装前请注意
API 密钥是作为 Bearer 凭据发送的秘密,请勿写入共享配置。监控会把序列更新推送到你提供的 webhook 地址,该地址及其接收方会看到相关数据。监控的创建和删除会改变账户状态。查询和问题会发送到 Starwell 服务。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Starwell: World Data & Statistics,将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Web executable,通过 Streamable HTTP。 远程服务在工作区中配置后即可从网页运行时运行。

交给智能体安装

把这段提示词粘贴到 Claude Code、Codex、Cursor 等智能体,或 SourceWeft 对话中。智能体会读取该服务器的安装指南,先向你展示发布者、端点和登录方式,经你同意后再把它添加到你的客户端。密钥不会写进任何命令。

阅读 https://sourceweft.com/mcp/dev.starwell%2Fworld-data-statistics/install.md,并按其中说明把这个 MCP 服务器接入我的客户端。修改任何配置之前,先告诉我它的发布者、端点和登录方式,等我确认。不要把 API 密钥写进命令或我会提交的文件;问我密钥应从哪里获取。

查看智能体所依据的安装指南

其他 MCP 客户端

把它添加到你客户端的 mcpServers 配置中。

{
  "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.

来源: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.

无需输入参数。

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.

输入参数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.

输入参数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.

输入参数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).

输入参数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.

输入参数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.

输入参数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).

无需输入参数。

delete_monitor

Delete one of your monitors

输入参数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.

输入参数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.

输入参数endstartseriesquestion必填

版本历史

1
  1. v0.2.2最新Sep 16, 2026

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