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 1856+ live data sources. This is an independent, unofficial integration — not affiliated with, endorsed by, or published by the upstream provider.

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.

Employment Projections. "Projected growth and annual openings for software developers" → bls_occupation_projections({ soc_code: "15-1252" }), or ({ query: "nurse" }), or rank occupations with ({ rank_by: "growth_percent", min_employment_thousands: 50 }). Serves the latest release's national employment matrix (employment, 10-year change, annual openings, median wage, typical entry education); employment and openings are in thousands, and the response carries the projection period and data_as_of. Earlier vintages are not served.

4. Local-area unemployment by place name. "What's the unemployment rate in Wake County, NC?" or "Cary, North Carolina" or "Fargo-Moorhead MSA" → bls_local_unemployment({place, state?}). This is the tool for LAUS (Local Area Unemployment Statistics) lookups by county / metro area / city — bls_search's curated catalog has no local-area entries, and constructing a LAUS series ID by hand requires a place → BLS area-code crosswalk (~8,000 US counties/metros/cities) that isn't something to guess at. bls_local_unemployment resolves the name against that crosswalk itself (bundled from BLS's la.area reference file), returns candidates when the name is ambiguous, and falls back to the county — saying so explicitly — when a city is below the LAUS city-reporting threshold.

Reading the response

bls_get_series returns each series newest first — the payload says so in observation_order, so you don't have to infer the direction from the dates. count is the number of points for that series, and BLS returns every point in the requested year range, so it is never a total sitting beside a shorter list.

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:

Don't try to construct national/state/industry IDs from scratch — use bls_search or bls_popular_series. For LAUS local-area IDs (county/MSA/city) specifically, use bls_local_unemployment({place, state?}) — it resolves the place name to the correct area code for you.

Update cadence

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 CPIAUCSL with the pc1 units 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 1856+ data sources. The only difference is which pack's tools are listed directly; ask_pipeworx reaches all of them from either one.

No MCP client? Call it over HTTP

curl -X POST https://gateway.pipeworx.io/v1/tools/bls_get_series \
  -H 'Content-Type: application/json' \
  -d '{"series_id":"LNS14000000"}'

No account needed for the first calls. Inspect any tool: GET https://gateway.pipeworx.io/v1/tools/bls_get_series. Find one: POST https://gateway.pipeworx.io/v1/tools/search_packs with {"query":"..."}.

Run it from npm

@pipeworx/mcp-bls is a local stdio bridge to the Pipeworx gateway: your MCP client starts it with npx, and it forwards every call to the same https://gateway.pipeworx.io/bls/mcp endpoint shown above. It needs network access; there is no offline mode.

{
  "mcpServers": {
    "bls": {
      "command": "npx",
      "args": ["-y", "@pipeworx/mcp-bls"]
    }
  }
}

Without a key it calls anonymously, capped at 50 calls a day. A free account raises that to 200 a day: get a key at https://pipeworx.io/signup and add "env": { "PIPEWORX_API_KEY": "<your key>" } to the server entry. The key is sent as a Bearer token, the same way a hosted connection sends it, so calls are metered and billed exactly as they are there.

It lists only this pack's tools by default. Set PIPEWORX_META_TOOLS=1 to also list ask_pipeworx and the other gateway-wide tools.

Behind an HTTPS proxy: Node's built-in fetch does not read HTTPS_PROXY by default. Newer Node releases honour it when NODE_USE_ENV_PROXY=1 is set; check your Node version's documentation.

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

• Docs and guides
• pipeworx.io

License

MIT