
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.
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
在 SourceWeft 中
- 打开 控制台中的 FRED (economic data),将其添加到工作区。
- 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
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:
- "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. - "What's the 10-year Treasury yield today?" —
get_latest(DGS10)→ 4.53% (it correctly skips the.rows daily series publish on holidays). - "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. - "Find me data on median household income." —
search_series→MEHOINUSA672N(real) andMEHOINUSA646N(nominal), annual. - "Is the labor market loosening? Compare unemployment and job openings
since 2024." —
compare_series([UNRATE, JTSJOL])→ one aligned table. - "What economic data comes out this week?" —
get_release_calendar(7)→ 241 release dates, CPI included. - "What was real GDP growth each quarter of 2025?" —
get_observations(A191RL1Q225SBEA)→ −0.6, +3.8, +4.4, +0.5%. - "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:
- "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. - "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. - "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. - "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)
Claude Code
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=0to disable caching,FRED_MCP_USER_AGENTto identify your own deployment.
Develop
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
-
.mcpbone-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版本历史
1- v0.1.1最新Sep 16, 2026
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