bls-labor-mcp-server

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  <h1>@cyanheads/bls-labor-mcp-server</h1>
  <p><b>Fetch US Bureau of Labor Statistics data — CPI, unemployment, wages, JOLTS, and more via MCP. STDIO or Streamable HTTP.</b>
  <div>7 Tools</div>
  </p>
</div>

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**Public Hosted Server:** [https://bls-labor.caseyjhand.com/mcp](https://bls-labor.caseyjhand.com/mcp)

</div>

---

## Tools

Seven tools in two groups — four for BLS data access (survey discovery, SeriesID resolution, history, current values) and three for optional DataCanvas SQL analysis of large result sets:

| 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` — provenance, TTL, row count, column schema. Requires `CANVAS_PROVIDER_TYPE=duckdb`. |
| `bls_dataframe_query` | Run a SELECT against canvas dataframes registered by `bls_get_series`. Supports JOINs, aggregates, window functions, CTEs. Requires `CANVAS_PROVIDER_TYPE=duckdb`. |
| `bls_dataframe_drop` | Drop a canvas dataframe by name. Opt-in via `BLS_DATAFRAME_DROP_ENABLED=true`; TTL handles cleanup by default. Requires `CANVAS_PROVIDER_TYPE=duckdb`. |

### `bls_list_surveys`

List available BLS survey programs and their metadata.

- Covers all major BLS programs: CPS, CES, CPI, PPI, JOLTS, LAUS, OEWS, ECEC, and others
- Optional `category` filter (`prices`, `employment`, `wages`, `productivity`, `injuries`, `time_use`)
- Returns survey codes, descriptions, and calculation-support flags (`allowsNetChange`, `allowsPercentChange`, `hasAnnualAverages`)
- Backed by the live BLS surveys API with monthly caching; does not consume daily API quota

---

### `bls_search_series`

The entry point for most BLS workflows. Resolves human concepts to BLS SeriesIDs.

- BLS identifiers like `LNS14000000` and `CES0000000001` encode survey + area + item + seasonal flag in opaque positional codes — this tool decodes them
- Free-text and keyword search against the full BLS series catalog
- Filter by survey code, geographic area (state name, MSA, or FIPS), and seasonal adjustment flag
- Returns decoded series components (survey, area, item, seasonal flag) alongside the plain-language name
- Operates entirely offline against LABSTAT flat files bundled at startup — no API quota consumed
- Use before `bls_get_series` or `bls_get_latest` when you have a concept but not a SeriesID

---

### `bls_get_series`

Fetch historical time-series data for one or more BLS series.

- Batch fetch up to 50 series per request (counts as one of the 500 daily API queries)
- Optional `start_year` / `end_year` window (BLS caps history at 20 years per request)
- Optional `calculations: true` for BLS-server-side net change and percent change — a survey returns whichever it supports (CPI/PPI return percent change only); check `bls_list_surveys` for per-survey support
- Returns observations with series metadata (title, area, item, seasonality)
- Spills to a DataCanvas dataframe when the observation count exceeds the inline context budget — response includes a `dataset.name` handle for SQL via `bls_dataframe_query`. Requires `CANVAS_PROVIDER_TYPE=duckdb`.

---

### `bls_get_latest`

Get the current value for one or more BLS series.

- Issues one GET per SeriesID (no batch-latest endpoint exists in BLS v2) — each counts as one of the 500 daily API queries
- Recommended limit: ≤10 series per call; accepts up to 50
- For "current value" across many series, `bls_get_series` with a narrow year window is more quota-efficient (one API query regardless of series count)
- Partial success reporting — failed series are returned in a separate `failed[]` array alongside successful results

---

### `bls_dataframe_describe`

Inspect canvas dataframes registered by `bls_get_series`.

- Lists all active dataframes for the current tenant: table name, source tool, query params, row count, column schema, TTL
- Optionally describe a single dataframe by name
- Lazy-sweeps expired entries before responding
- Use before writing SQL to confirm column names

---

### `bls_dataframe_query`

Run SQL against canvas dataframes registered by `bls_get_series`.

- Read-only: writes, DDL, DROP, COPY, PRAGMA, ATTACH, and external-file table functions are rejected
- Supports JOINs, aggregates, window functions, and CTEs
- Optional `register_as` persists the query result as a new named dataframe with a fresh TTL — useful for chaining analyses without re-consuming BLS API quota
- Inline row cap: 1,000 rows by default (max 10,000); full results live on-canvas when `register_as` is set
- Zero BLS API quota consumed

---

### `bls_dataframe_drop`

Drop a canvas dataframe by name. Idempotent — returns `dropped: false` when nothing matched.

- Use to free canvas resources ahead of the per-table TTL when an analysis is complete
- Must be explicitly enabled via `BLS_DATAFRAME_DROP_ENABLED=true` (TTL handles cleanup by default)

## Features

Built on [`@cyanheads/mcp-ts-core`](https://www.npmjs.com/package/@cyanheads/mcp-ts-core):

- Declarative tool definitions — single file per tool, framework handles registration and validation
- Unified error handling across all tools
- Pluggable auth (`none`, `jwt`, `oauth`)
- Swappable storage backends: `in-memory`, `filesystem`, `Supabase`, `Cloudflare KV/R2/D1`
- Structured logging with optional OpenTelemetry tracing
- STDIO and Streamable HTTP transports

BLS-specific:

- BLS API v2 integration with retry/backoff and daily quota tracking
- Offline series catalog search against LABSTAT flat files — zero API quota for discovery
- Typed error contracts for BLS-specific failure modes: quota exhaustion, locked database, calculations not supported
- Period-over-period calculations via BLS server-side flag (consistent with BLS published numbers)
- DataCanvas spillover (DuckDB) for large multi-series result sets — SQL access without re-querying the API
- Optional local observation mirror — sync LABSTAT bulk data into an embedded SQLite store to serve `bls_get_series` / `bls_get_latest` without the 500/day API cap (opt-in, off by default)
- On-disk SQLite catalog index — the series catalog is parsed into an FTS5 SQLite store, queried on demand (not held in memory) and persisted across restarts; the OES/OEWS wage survey (~6M series) is opt-in via `BLS_CATALOG_INCLUDE_OES`

## Getting started

Add the following to your MCP client configuration file. A free BLS API key unlocks 500 queries/day — register at [bls.gov/developers](https://www.bls.gov/developers/home.htm). The server works without a key at 25 req/day.

```json
{
  "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):

```json
{
  "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:

```json
{
  "mcpServers": {
    "bls-labor-mcp-server": {
      "type": "stdio",
      "command": "docker",
      "args": ["run", "-i", "--rm", "-e", "MCP_TRANSPORT_TYPE=stdi