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BLS MCP — Bureau of Labor Statistics public data API (v2)
About
BLS MCP — Bureau of Labor Statistics public data API (v2)
Remote endpoints: streamable-http: https://gateway.pipeworx.io/bls/mcp
Security Report
Valid MCP server (1 strong, 0 medium validity signals). No known CVEs in dependencies. Imported from the Official MCP Registry. Trust signals: trusted author (123/123 approved). 1 finding(s) downgraded by scanner intelligence.
5 tools verified · Open access · 1 issue found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
Permissions Required
This plugin requests these system permissions. Most are normal for its category.
How to Connect
Remote Plugin
No local installation needed. Your AI client connects to the remote endpoint directly.
Add this to your MCP configuration to connect:
{
"mcpServers": {
"io-github-pipeworx-io-bls": {
"url": "https://gateway.pipeworx.io/bls/mcp"
}
}
}Documentation
View on GitHubFrom the project's GitHub README.
BLS — Bureau of Labor Statistics
The U.S. Bureau of Labor Statistics's data warehouse. Employment, unemployment, wages, prices (CPI/PPI), productivity, occupational projections — the official US labor and price data. National, state, and metro level. Free with a registered API key.
Part of Pipeworx — an MCP gateway connecting AI agents to 1476+ live data sources.
Why this matters for AI agents
Anything labor-market or inflation-related at the official level: BLS. Where FRED gives you headline series, BLS gives you the underlying detail (occupation-level, industry-level, MSA-level). Agents researching local economic conditions, sector wages, or specific CPI components reach BLS directly.
Three core flows:
1. Look up a series. "What's the metro Denver unemployment rate?" → bls_search({query: "Denver unemployment"}) → series IDs. Then bls_get_series({series_id}) for values.
2. Latest value. "What's national unemployment right now?" → bls_latest({series_id: "LNS14000000"}) → most recent observation.
3. Browse popular series. "What does BLS publish?" → bls_popular_series → curated list of high-traffic IDs.
Auth
BLS API requires a free key from https://www.bls.gov/developers/. Without it, calls are throttled to ~25/day per IP. With a key, it's 500/day. Pass via _apiKey per call.
Series ID structure
BLS series IDs encode survey, area, sector, and data type. Examples:
| Series ID | What it is |
|---|---|
LNS14000000 | National unemployment rate (seasonally adjusted) |
CES0000000001 | Total nonfarm employment (national) |
CUUR0000SA0 | CPI all items, US city average, not seasonally adjusted |
LAUMT080000000000003 | Denver MSA unemployment rate |
WPSFD49207 | PPI for finished goods |
Don't try to construct IDs from scratch — use bls_search or bls_popular_series.
Update cadence
| Data | Release timing |
|---|---|
| Employment situation (national + state) | First Friday of the month |
| CPI | Mid-month (around the 10th-15th) |
| PPI | Mid-month, day after CPI |
| Metro unemployment (LAUS) | ~3 weeks after the reference month |
| Productivity | Quarterly, ~5 weeks after quarter end |
Pipeworx caches BLS responses with TTLs aligned to release schedules.
Common pitfalls
- Seasonal adjustment. Same series exists in seasonally-adjusted (SA) and not-seasonally-adjusted (NSA) variants. Check the series ID prefix (
LNS= SA,LNU= NSA). Mixing them is the most common analyst error. - Annual averages vs monthly. Some IDs return only annual data; others return monthly. Read the metadata before plotting trends.
- State and metro coverage. Not every series exists at every geography. Smaller metros have larger lags and more imputed values.
- Inflation vs CPI. "Inflation" usually means CPI year-over-year change. To get YoY, request 13 months and compute, or use FRED's
CPIAUCSLwith thepc1units transformation (which does it for you).
Quick Start
Add to your MCP client (Claude Desktop, Cursor, Windsurf, etc.):
{
"mcpServers": {
"bls": {
"url": "https://gateway.pipeworx.io/bls/mcp"
}
}
}
What this endpoint actually serves
tools/list at https://gateway.pipeworx.io/bls/mcp returns the tools in the table
above plus the shared Pipeworx meta-tools — ask_pipeworx,
discover_tools, search_within, remember/recall and the rest of the
gateway-wide set. So the tool count you see is larger than this table: a
single-pack endpoint currently lists roughly 30 shared tools alongside the
pack's own. The connection's initialize response states its exact scope, and
is the authoritative answer for a given day.
This is deliberate, not multiplexing by accident. The meta-tools are what let a
scoped connection answer a question this pack does not cover — via
ask_pipeworx, which routes across the whole catalog — without you adding a
second MCP server. There is currently no way to mount a pack endpoint without
them; if the extra schemas cost you more context than the routing is worth,
connect to the full gateway once rather than to several pack endpoints.
Or connect to the full Pipeworx gateway to get every pack's tools listed directly, instead of just this one's:
{
"mcpServers": {
"pipeworx": {
"url": "https://gateway.pipeworx.io/mcp"
}
}
}
Both URLs reach the same gateway and the same 1476+ data sources. The
only difference is which pack's tools are listed directly; ask_pipeworx
reaches all of them from either one.
Using with ask_pipeworx
Instead of calling tools directly, you can ask questions in plain English — this works on the pack endpoint above as well as on the full gateway:
ask_pipeworx({ question: "your question about Bls data" })
The gateway picks the right tool and fills the arguments automatically.
More
License
MIT
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