FRED (economic data)

io.github.mcpwright由 GitHub 账号 mcpwright 发布v0.1.1更新于 Oct 24, 2026

FRED economic time series + ALFRED vintages: data as originally published, before revisions.

已验证STDIO仅桌面金融数据与分析

概览

AI 生成的概览

只读的 FRED 与 ALFRED 经济时间序列 MCP 服务器,让助手搜索、比较并读取美国及国际数据,包括当时发布的原始版本。

可以做什么
  • 按自由文本搜索序列,并读取序列的元数据与说明
  • 读取指定日期区间的观测值(支持变换与降采样)、最新值及下次发布日期
  • 将 2 至 5 个序列对齐到同一时间轴比较,并查询即将发布的数据日历
  • 查询 ALFRED 版本数据:某序列在过去某日的已知状态、单个数据点的完整修订历史,以及序列的修订日期
适用场景
当助手需要权威的美国及国际经济数据、发布日历,或需要区分最初公布值与今日修订值时适用,例如分析决策者在某一时点所掌握的数据。
运行要求
以 stdio 在本地运行,通常通过 uvx 启动 mcpwright-fred 包,需要 Python/uv 运行环境。需要自备免费 FRED API 密钥,放在 FRED_API_KEY 中;FRED_MCP_USER_AGENT 为可选项。需要访问 FRED API 的网络连接。
安装前请注意
FRED API 密钥按 FRED 使用条款属于个人密钥,须自行提供。部分序列由第三方拥有版权并附带其条款,超出个人使用范围时需自行遵守。该服务器为只读,且与圣路易斯联邦储备银行无隶属或背书关系。

安装

在 SourceWeft 中

  1. 打开 控制台中的 FRED (economic data),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。

Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。

其他 MCP 客户端

参照 仓库 中的启动说明。

README

fred-mcp

FRED® economic data inside your AI agent — including what the numbers said before the revisions. An MCP server for the Federal Reserve Bank of St. Louis's FRED® API: search and read 800,000+ U.S. and international time series, follow the release calendar, and — the distinctive part — query ALFRED® vintage data: any series exactly as it was known on a past date, and any single data point's full revision history from its initial print to today's value.

Read-only, built on public endpoints, powered by your own free FRED API key. Live API calls with a volatility-aware cache (vintage reads are immutable and cache long; current data stays fresh) — no bulk mirroring.

This product uses the FRED® API but is not endorsed or certified by the Federal Reserve Bank of St. Louis. By using this server you agree to the FRED® API Terms of Use.

Status: v0.1.0 — live on PyPI (uvx mcpwright-fred) and the official MCP Registry (io.github.mcpwright/fred-mcp). 9 tools, CI-gated, built on mcpwright-core.

Why vintage data matters

Economic numbers get revised — sometimes dramatically. The advance estimate of Q4-2008 real GDP told policymakers the economy was shrinking far more slowly than the number that stands today. If an agent reasons about what decision-makers knew at the time using current data, it is quietly wrong. get_series_as_of and get_revision_history make as-published data a first-class question.

Tools

ToolWhat it does
search_seriesFind series IDs by free text, best matches first
get_seriesOne series' full metadata + verbatim notes
get_observationsA date window of values; transforms (pct_change_yoy, …) + downsampling
get_latestThe most recent value + the next scheduled release date
compare_series2–5 series aligned on one date axis
get_release_calendarUpcoming data releases ("when's the next jobs report?")
get_series_as_of ⭐A series exactly as known on a past date (ALFRED vintage)
get_revision_history ⭐One data point's life: initial print → every revision → today
get_vintage_dates ⭐When a series was released/revised; bounds the vintage tools

All tools are read-only and annotated as such.

What can you ask?

Every question below was run live against the real FRED API through these tools (answers as of June 2026 — ask again and they'll be current).

Everyday questions:

  1. "What's the unemployment rate right now, and when's the next jobs report?" — get_latest(UNRATE) → 4.3% (May 2026), next release 2026-07-02.
  2. "What's the 10-year Treasury yield today?" — get_latest(DGS10) → 4.53% (it correctly skips the . rows daily series publish on holidays).
  3. "How has inflation trended over the past year?" — get_observations(CPIAUCSL, transform=pct_change_yoy) → 2.4% → 3.3% → 3.8% → 4.2% over Feb–May 2026.
  4. "Find me data on median household income." — search_series → MEHOINUSA672N (real) and MEHOINUSA646N (nominal), annual.
  5. "Is the labor market loosening? Compare unemployment and job openings since 2024." — compare_series([UNRATE, JTSJOL]) → one aligned table.
  6. "What economic data comes out this week?" — get_release_calendar(7) → 241 release dates, CPI included.
  7. "What was real GDP growth each quarter of 2025?" — get_observations(A191RL1Q225SBEA) → −0.6, +3.8, +4.4, +0.5%.
  8. "Give me CPI as annual averages for the 2020s." — get_observations(CPIAUCSL, frequency=annual) → one row per year.

Questions only the vintage tools can answer:

  1. "How bad did Q4-2008 GDP look to policymakers in early 2009, versus what we know now?" — get_series_as_of(GDPC1, "2009-02-15") → a −3.8% annualized decline as known then (in chained-2000 dollars — the metadata is vintage-pinned too) versus −8.5% in today's data. Policy ran on the first number.
  2. "Was the May 2020 COVID unemployment rate ever revised?" — get_revision_history(UNRATE, "2020-05-01") → first published as 13.3 (2020-06-05), currently 13.2, with each revision dated.
  3. "What mortgage rate did the Fed see going into the March 2022 liftoff meeting?" — get_series_as_of(MORTGAGE30US, "2022-03-16") → 3.85% as known then; 6.48% today.
  4. "How often does GDP actually get revised?" — get_vintage_dates(GDPC1) → 415 vintages since 1991-12-04.

Install

You need a free FRED API key (takes seconds): https://fred.stlouisfed.org/docs/api/api_key_request.html. Keys are personal under the FRED terms — bring your own.

uvx (any MCP client)

json
{  "mcpServers": {    "fred": {      "command": "uvx",      "args": ["mcpwright-fred"],      "env": { "FRED_API_KEY": "your-key-here" }    }  }}

Claude Code

bash
claude mcp add fred -e FRED_API_KEY=your-key-here -- uvx mcpwright-fred

Claude Desktop

Use the one-click .mcpb extension from the latest release (it prompts for your API key), or add the uvx JSON above to your claude_desktop_config.json.

OpenAI Agents SDK / other clients

Any MCP-capable client works — point it at uvx mcpwright-fred over stdio with FRED_API_KEY in the environment.

Notes

  • Revisions: current values often differ from what was originally published; for "what was known at the time", use the vintage tools.
  • Copyrighted series: some FRED series are owned by third parties; their notes carry the owner's terms (surfaced verbatim, flagged via copyrighted). You are responsible for complying with them beyond personal use.
  • Caching & rate limits: responses are cached in-memory (vintage reads long, live reads short) and requests are throttled well under FRED's rate limit. Set FRED_MCP_CACHE=0 to disable caching, FRED_MCP_USER_AGENT to identify your own deployment.

Develop

bash
git clone https://github.com/mcpwright/fred-mcp && cd fred-mcpuv syncuv run pytest                                  # testsuv run mypy                                    # typesuv run ruff check src/ && uv run ruff format --check src/   # lint + formatuv run pre-commit run --all-files              # everything, like CI

Dev loop: feature branch → PR → Code Quality & Tests green → squash-merge.

Roadmap

  • v1 tool surface (9 tools incl. the ALFRED vintage lane)
  • Publish to PyPI (mcpwright-fred) + the MCP Registry
  • Site page at mcpwright.com/fred
  • .mcpb one-click Claude Desktop extension (v0.1.0 release)
  • GeoFRED / maps (pairs with census-mcp)

Questions & feedback

Discussions for questions and ideas · Issues for bugs.


Part of mcpwright — polished MCP servers for authoritative public data · built by Devender Gollapally. FRED® and ALFRED® are registered trademarks of the Federal Reserve Bank of St. Louis. This project is not affiliated with, endorsed, or certified by the Federal Reserve Bank of St. Louis.

来源:README.md,提交 96ed8d6

工具

0
SourceWeft 尚未在沙箱中启动过该软件包,因此其工具未知。

版本历史

1
  1. v0.1.1最新Sep 16, 2026

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