
Wraps the Bureau of Labor Statistics v2 API with a focus on resolving cryptic SeriesIDs before you fetch data. You get natural language search against the full LABSTAT catalog to turn "unemployment rate" into LNS14000000, then pull time series for CPI, CES, JOLTS, wages, and 20+ other BLS surveys. Handles batching (50 series per request), year windows, and server-side calculations when the survey supports them. Results that exceed the context budget spill to DataCanvas dataframes, which you can query with SQL, join across surveys, or persist for later analysis. The search runs offline against bundled flat files, so it doesn't burn your 500-query daily quota. Reach for this when you need authoritative US labor data without decoding positional survey codes by hand.
Fetch US Bureau of Labor Statistics data — CPI, unemployment, wages, JOLTS, and more via MCP. STDIO or Streamable HTTP.
Public Hosted Server: https://bls-labor.caseyjhand.com/mcp
US labor statistics from the Bureau of Labor Statistics public API v2 and LABSTAT flat-file catalog. Resolve opaque SeriesIDs from natural language, fetch historical time-series or the latest observation, and query large multi-series results with SQL through an optional DataCanvas. Runs as a stdio process, a local Streamable HTTP server, or the public hosted endpoint above.
| Tool | Description |
|---|---|
bls_list_surveys | List BLS survey programs (CPI, CPS, CES, JOLTS, PPI, OEWS, …) with codes, descriptions, and calculation-support flags. |
bls_search_series | Search the BLS series catalog by natural language, survey, area, or keywords to resolve cryptic SeriesIDs. |
bls_get_series | Fetch time-series data for 1–50 BLS series by SeriesID, with optional year range and period-over-period calculations. |
bls_get_latest | Return the single most recent observation for one or more BLS series. |
bls_dataframe_describe | List canvas dataframes registered by bls_get_series or bls_dataframe_query — provenance, TTL, row count, column schema. Available when CANVAS_PROVIDER_TYPE=duckdb. |
bls_dataframe_query | Run a SELECT against canvas dataframes registered by bls_get_series or an earlier register_as. Supports JOINs, aggregates, window functions, CTEs. Available when CANVAS_PROVIDER_TYPE=duckdb. |
bls_dataframe_drop | Drop a canvas dataframe by name. Available when CANVAS_PROVIDER_TYPE=duckdb and BLS_DATAFRAME_DROP_ENABLED=true; TTL handles cleanup by default. |
bls_list_surveys toolcategory filters survey programs by subject; returns codes, names, and calculation-support flags (allowsNetChange, allowsPercentChange, hasAnnualAverages).bls_get_series's annualAverageRows for the rows actually returned.bls_search_series toolsurvey, area (substring of area, title, or SeriesID), and seasonal_adjustment; blank filters are omitted. limit is 1–50 (default 10), with offset pagination; without an area filter, equally matching national series rank first.frequency. Follow nextOffset while truncated is true; capped: true makes totalCount a lower bound, and paging stops at the FTS candidate pool.BLS_CATALOG_INCLUDE_OES. Unindexed surveys remain fetchable by SeriesID.bls_get_series toolstart_year/end_year window of up to 20 years, optional calculations, and annual_average. A start alone resolves the end to the current year capped at start + 19; an end alone is rejected. One batch consumes one API query; calculations depend on survey support (CPI/PPI return percent change only).available, preserves the raw - missing-value sentinel, and keeps valid series in mixed batches. Enrichment reports the applied year window, calculations, and annual-average rows.dataset.name when CANVAS_PROVIDER_TYPE=duckdb; otherwise canvas_unavailable asks for a narrower window.bls_get_latest toolbls_get_series for a more efficient multi-series batch.results[] beside per-series failed[] entries. latestObservation.available distinguishes a published value from BLS's missing-value sentinel.bls_dataframe_describe toolname describes one registered dataframe; omit it to list active dataframes for the tenant. Requires CANVAS_PROVIDER_TYPE=duckdb.created_at/expires_at), and column_schema; BLS columns are nullable. Registered-query types outside the canvas set (DECIMAL, HUGEINT, SMALLINT, lists) report as VARCHAR. Expired entries are removed when their canvas drop succeeds.bls_dataframe_query toolrow_limit defaults to 1000 and caps at 10000; writes, external-file reads, and system catalogs are denied.register_as stages the result with a fresh TTL for chained analysis; requires CANVAS_PROVIDER_TYPE=duckdb.bls_dataframe_drop toolname identifies the dataframe to drop. Available only with CANVAS_PROVIDER_TYPE=duckdb and BLS_DATAFRAME_DROP_ENABLED=true; TTL handles cleanup by default.dropped: false for a missing table. A failed drop returns retryable canvas_drop_failed and leaves the dataframe registered.Built on @cyanheads/mcp-ts-core: stdio and Streamable HTTP transports, pluggable auth (none / jwt / oauth), swappable storage (in-memory, filesystem, Supabase, Cloudflare KV/R2/D1), structured logging with optional OpenTelemetry tracing.
BLS-specific:
BLS_CATALOG_INCLUDE_OESAgent-friendly output:
dataset.name handle plus row count and expiry; bls_search_series echoes effectiveQuery, catalogSize, and whether the FTS candidate pool was cappedbls_get_latest returns per-item failed[] (seriesId + error) alongside successful results[] instead of failing the whole batch; bls_get_series keeps valid series when another SeriesID in the same batch is invalid or emptyavailable boolean for BLS's - missing-value sentinel, so callers branch on a typed field instead of parsing raw valuesenrichment.notice explains empty results, canvas spillover, and unavailable data with concrete next steps (e.g. using bls_search_series to verify a SeriesID)A public instance is available at https://bls-labor.caseyjhand.com/mcp — no installation required. Point any MCP client at it via Streamable HTTP:
{
"mcpServers": {
"bls-labor-mcp-server": {
"type": "streamable-http",
"url": "https://bls-labor.caseyjhand.com/mcp"
}
}
}
Add the following to your MCP client configuration file. A free BLS API key unlocks 500 queries/day — register at bls.gov/developers. The server works without a key at 25 req/day.
{
"mcpServers": {
"bls-labor-mcp-server": {
"type": "stdio",
"command": "bunx",
"args": ["@cyanheads/bls-labor-mcp-server@latest"],
"env": {
"MCP_TRANSPORT_TYPE": "stdio",
"MCP_LOG_LEVEL": "info",
"BLS_API_KEY": "your-key-here"
}
}
}
}
Or with npx (no Bun required):
{
"mcpServers": {
"bls-labor-mcp-server": {
"type": "stdio",
"command": "npx",
"args": ["-y", "@cyanheads/bls-labor-mcp-server@latest"],
"env": {
"MCP_TRANSPORT_TYPE": "stdio",
"MCP_LOG_LEVEL": "info",
"BLS_API_KEY": "your-key-here"
}
}
}
}
Or with Docker:
{
"mcpServers": {
"bls-labor-mcp-server": {
"type": "stdio",
"command": "docker",
"args": ["run", "-i", "--rm", "-e", "MCP_TRANSPORT_TYPE=stdio", "-e", "BLS_API_KEY=your-key-here", "ghcr.io/cyanheads/bls-labor-mcp-server:latest"]
}
}
}
For Streamable HTTP, set the transport and start the server:
MCP_TRANSPORT_TYPE=http MCP_SESSION_MODE=stateless MCP_HTTP_PORT=3010 BLS_API_KEY=... bun run start:http
# Server listens at http://localhost:3010/mcp
git clone https://github.com/cyanheads/bls-labor-mcp-server.git
cd bls-labor-mcp-server
bun install
cp .env.example .env
# edit .env and set BLS_API_KEY
All configuration is validated at startup via Zod schemas in src/config/server-config.ts.
| Variable | Description | Default |
|---|---|---|
BLS_API_KEY | BLS v2 API key. Optional — 25 req/day without, 500 req/day with. Register free at bls.gov/developers. | — |
BLS_BASE_URL | BLS API v2 base URL. | https://api.bls.gov/publicAPI/v2 |
BLS_CATALOG_BASE_URL | LABSTAT flat-file base URL. Override to point at a local mirror. | https://download.bls.gov/pub/time.series |
BLS_CATALOG_DB_PATH | On-disk SQLite catalog index — queried on demand and persisted across restarts. Empty uses an in-memory DB (re-harvested each boot). Mount a volume here in containers. | .cache/bls-catalog.db |
BLS_CATALOG_CACHE_TTL_HOURS | Catalog freshness window in hours — re-harvest once the index is older, checked at startup and hourly while running. | 168 (7 days) |
BLS_CATALOG_INCLUDE_OES | Include the OES/OEWS wage survey (~6M series / ~1.2 GB; multi-minute first harvest). Off by default — OES series stay fetchable by ID. | false |
BLS_OBSERVATIONS_MIRROR_ENABLED | Serve observations from a local SQLite mirror instead of the live API (requires a one-time bootstrap — see below). | false |
BLS_DATASET_TTL_SECONDS | Per-dataframe TTL for canvas-registered tables, in seconds. | 86400 (24 h) |
BLS_DATAFRAME_DROP_ENABLED | Expose bls_dataframe_drop. TTL handles cleanup by default. | false |
CANVAS_PROVIDER_TYPE | Set to duckdb to enable DataCanvas tabular spillover for large result sets. | none |
MCP_TRANSPORT_TYPE | Transport: stdio or http. | stdio |
MCP_HTTP_PORT | HTTP server port. | 3010 |
MCP_SESSION_MODE | Session mode. This server uses stateless; valid schema values are auto, stateful, and stateless. Schema-default auto resolves to stateful. | stateless |
MCP_AUTH_MODE | Auth mode: none, jwt, or oauth. | none |
MCP_LOG_LEVEL | Log level (RFC 5424). | info |
LOGS_DIR | Directory for log files (Node.js only). | <project-root>/logs |
OTEL_ENABLED | Enable OpenTelemetry instrumentation. | false |
OTEL_EXPORTER_OTLP_ENDPOINT | Base OTLP URL for traces and metrics; signal-specific endpoints override it. | — |
OTEL_EXPORTER_OTLP_LOGS_ENDPOINT | Opt-in OTLP log endpoint. The base URL never enables log export. | — |
LOG_TOOL_FAILURE_PAYLOADS | Log failed-call arguments and results, redacted by key name; secrets in free-form values remain. | false |
LOG_TOOL_FAILURE_PAYLOAD_MAX_BYTES | UTF-8 byte cap per logged failure payload. | 16384 |
See .env.example for the full list of optional overrides.
For high-volume workloads, an opt-in local mirror serves bls_get_series / bls_get_latest from an embedded SQLite store instead of the BLS API — eliminating the 500/day quota cap. It is off by default. To enable:
Set BLS_OBSERVATIONS_MIRROR_ENABLED=true (and review the BLS_OBSERVATIONS_MIRROR_* vars in .env.example).
Run the one-time bootstrap out-of-band — it downloads the full LABSTAT observation set and can take a while:
node dist/services/bls-observations/subprocess.js --init
The mirror harvests every survey in the catalog's survey list — OE included, whatever BLS_CATALOG_INCLUDE_OES says — so it covers CM and CI too (about 55 MB of cm.data.* / ci.data.* files). An incremental refresh reads only files published after the mirror's last one, so a mirror bootstrapped before CM and CI joined picks each file up at its next BLS publication; until then those series come from the live API when fallback is on. Until the bootstrap completes, requests fall back to the live API (unless BLS_OBSERVATIONS_MIRROR_FALLBACK_LIVE=false). When a live fallback fails — quota exhausted, BLS unreachable — the series the mirror served are still returned, and enrichment.notice names each unserved SeriesID with the failure's reason and recovery. Mirror rows carry no BLS calculations: with calculations: true, a mirror-served series comes back without calculation fields, enrichment.calculationsApplied is false, and the notice names it. On HTTP transport, an incremental refresh runs on the BLS_OBSERVATIONS_MIRROR_REFRESH_CRON schedule. In containers, mount a persistent volume at BLS_OBSERVATIONS_MIRROR_PATH.
Upgrading an existing mirror. A mirror bootstrapped before sentinel rows were stored is missing the periods BLS publishes with its - missing-value marker. Opening such a mirror clears its sync checkpoint once, so the next refresh re-reads every LABSTAT file and fills them in — no operator action beyond letting that refresh run, and it takes as long as a full read. The mirror keeps serving throughout.
Build and run:
# One-time build
bun run rebuild
# Run the built server
bun run start:stdio
# or
bun run start:http
Run checks and tests:
bun run devcheck # Lint, format, typecheck, security
bun run test # Vitest test suite
bun run lint:mcp # Validate MCP definitions against spec
docker build -t bls-labor-mcp-server .
docker run --rm -e BLS_API_KEY=your-key -e MCP_TRANSPORT_TYPE=http -p 3010:3010 bls-labor-mcp-server
The Dockerfile defaults to HTTP transport, stateless session mode, and logs to /var/log/bls-labor-mcp-server. OpenTelemetry peer dependencies are installed by default — build with --build-arg OTEL_ENABLED=false to omit them.
| Directory | Purpose |
|---|---|
src/index.ts | createApp() entry point — registers tools and initializes services. |
src/config | Server-specific environment variable parsing and validation with Zod. |
src/mcp-server/tools | Tool definitions (*.tool.ts). |
src/services/bls-api | BLS API v2 service — batch fetch, latest-value GET, surveys metadata. |
src/services/bls-catalog | LABSTAT flat-file catalog — offline series index and search. |
src/services/bls-observations | Optional LABSTAT observation mirror — embedded SQLite store, ingester, and refresh subprocess. |
src/services/bls-periods | Annual-average period semantics (M13/Q05/S03) shared by the API and mirror paths. |
src/services/canvas-bridge | DataCanvas bridge — dataframe registration, SQL gate, lifecycle management. |
docs/design.md | Full tool surface specification, service architecture, and error contracts. |
tests/ | Unit and integration tests mirroring src/. |
See CLAUDE.md for development guidelines and architectural rules. The short version:
try/catch in tool logicctx.log for request-scoped logging, ctx.state for tenant-scoped storagebls_search_series is the anchor tool — design workflows to call it before the API toolsIssues are welcome. Run checks and tests before submitting:
bun run devcheck
bun run test
Apache-2.0 — see LICENSE for details.
BLS_API_KEYOptional — works without one (25 req/day). With key: 500 req/day + calculations and annual averages. Register free at bls.gov/developers.
MCP_LOG_LEVELdefault: infoSets the minimum log level for output (e.g., 'debug', 'info', 'warn').
MCP_HTTP_HOSTdefault: 127.0.0.1The hostname for the HTTP server.
MCP_HTTP_PORTdefault: 3010The port to run the HTTP server on.
MCP_HTTP_ENDPOINT_PATHdefault: /mcpThe endpoint path for the MCP server.
MCP_AUTH_MODEdefault: noneAuthentication mode to use: 'none', 'jwt', or 'oauth'.