Fred Mcp — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited Fred Mcp (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
<!-- mcp-name: io.github.mcpwright/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.
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.
| Tool | What it does |
|---|---|
search_series | Find series IDs by free text, best matches first |
get_series | One series' full metadata + verbatim notes |
get_observations | A date window of values; transforms (pct_change_yoy, …) + downsampling |
get_latest | The most recent value + the next scheduled release date |
compare_series | 2–5 series aligned on one date axis |
get_release_calendar | Upcoming 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.
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:
report?"* — get_latest(UNRATE) → 4.3% (May 2026), next release 2026-07-02.
get_latest(DGS10) → 4.53%(it correctly skips the . rows daily series publish on holidays).
get_observations(CPIAUCSL, transform=pct_change_yoy) → 2.4% → 3.3% → 3.8% → 4.2% over Feb–May 2026.
search_series →MEHOINUSA672N (real) and MEHOINUSA646N (nominal), annual.
since 2024."* — compare_series([UNRATE, JTSJOL]) → one aligned table.
get_release_calendar(7) →241 release dates, CPI included.
get_observations(A191RL1Q225SBEA) → −0.6, +3.8, +4.4, +0.5%.
get_observations(CPIAUCSL, frequency=annual) → one row per year.
Questions only the vintage tools can answer:
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.
get_revision_history(UNRATE, "2020-05-01") → first published as 13.3 (2020-06-05), currently 13.2, with each revision dated.
meeting?"* — get_series_as_of(MORTGAGE30US, "2022-03-16") → 3.85% as known then; 6.48% today.
get_vintage_dates(GDPC1)→ 415 vintages since 1991-12-04.
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){
"mcpServers": {
"fred": {
"command": "uvx",
"args": ["mcpwright-fred"],
"env": { "FRED_API_KEY": "your-key-here" }
}
}
}claude mcp add fred -e FRED_API_KEY=your-key-here -- uvx mcpwright-fredUse 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.
Any MCP-capable client works — point it at uvx mcpwright-fred over stdio with FRED_API_KEY in the environment.
published; for "what was known at the time", use the vintage tools.
notes carry the owner's terms (surfaced verbatim, flagged via copyrighted). You are responsible for complying with them beyond personal use.
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.
git clone https://github.com/mcpwright/fred-mcp && cd fred-mcp
uv sync
uv run pytest # tests
uv run mypy # types
uv run ruff check src/ && uv run ruff format --check src/ # lint + format
uv run pre-commit run --all-files # everything, like CIDev loop: feature branch → PR → Code Quality & Tests green → squash-merge.
mcpwright-fred) + the MCP Registry.mcpb one-click Claude Desktop extension (v0.1.0 release)Discussions for questions and ideas · Issues for bugs.
Part of [mcpwright](https://mcpwright.com) — 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.
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.