BLS OEWS

io.github.1102tools由 GitHub 帳號 1102tools 發布v0.2.7更新於 Oct 24, 2026

BLS Occupational Employment and Wage Statistics market wages. 7 tools.

概覽

AI 產生的概覽

以隨套件附帶的 BLS OEWS 資料回答美國職業薪資問題,包含都會區比較與 IGCE 薪資基準。

可以做什麼
從隨套件附帶的唯讀資料庫提供 BLS 職業就業與薪資統計,因此回答在本機完成,並標註資料版本、發布日期、擷取日期與來源檔案。工具涵蓋依 SOC 代碼查詢全國、州或都會區薪資,跨都會區或跨職業比較,含負擔率估算的 IGCE 薪資基準,SOC 與都會區代碼查詢,以及資料狀態報告。當 BLS 未公布某項數值時,會保留 BLS 註腳並建議替代指標。
適用情境
適合價格分析、IGCE 編製與勞動市場研究,需要某職業或地區的市場薪資資料而不想直接查詢 BLS 時使用。也適合核對某個報價時薪是否與已公布的市場資料相符。
執行需求
以 PyPI 套件在桌面 MCP 用戶端本機執行(uvx bls-oews-mcp),僅支援桌面端。不需要 API 金鑰;選用的 BLS_API_KEY 環境變數用於 BLS v2 API。首次使用會把約 50 MB 的資料庫解壓縮到使用者快取目錄,可用 BLS_OEWS_DATA_DIR 更改位置。建議的設定使用套件重新整理參數,會在啟動時增加網路等待時間。
安裝前請注意
薪資資料是雇主申報的基本薪資,不含福利、管理費、G&A 與利潤,因此負擔率是由乘數估算得出,並非 BLS 資料。資料為隨套件附帶的版本,落後約一年,且不會自動更新。被截尾的薪資保留 BLS 公布的區間下限。選用的 BLS_API_KEY 屬於憑證,應透過環境變數提供,不要外洩。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 BLS OEWS,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

README

bls-oews-mcp

[price: free] [license: MIT] [tools: 8] [regression tests]

Free, open-source MCP server for BLS Occupational Employment and Wage Statistics (OEWS) market wages. For IGCE development, price analysis, and labor market research.

Overview, demo video and hosted setup: https://1102tools.com/mcp/bls-oews

No API key and no daily limit. The package bundles the current OEWS release (May 2025 estimates, published by BLS on May 15, 2026) as a read-only database built from BLS's published flat files, so every answer is local and each result cites the BLS release, publication date, retrieval date, and source file. See Local or hosted.

When BLS publishes no number for a wage measure, answers keep the BLS footnote that explains why and suggest the published hourly or annual alternative. Top-coded wages keep BLS's published lower bound; the server does not invent an exact wage or annualize hourly-only occupations.

Regression tests, and realistic contracting wage questions checked against BLS source values before release. See testing.md.

Local or hosted

Local (desktop)Claude (hosted)ChatGPT (hosted)
Local setupInstallInstall
  • Local runs it on your computer, inside the Claude or ChatGPT desktop app or another AI app. Answers come from the bundled BLS database, with no government API calls or request limits. It doesn't update itself, so ask your AI to update it. You don't have to set it up by hand: give your AI this page's link and ask it to set it up or walk you through it.
  • Hosted is always up to date, needs no setup or keys, and works in Claude or ChatGPT anywhere.

Compare local and hosted · Matching prompts

What it does

Answers OEWS questions from the bundled release through 8 MCP tools:

Core

  • get_wage_data - Wage statistics for an occupation by SOC code (national, state, or metro)
  • compare_metros - Compare wages for one occupation across multiple metro areas
  • compare_occupations - Compare wages across multiple occupations in one location

Workflow

  • igce_wage_benchmark - Wage benchmarks with burdened rate estimates for IGCE development
  • detect_latest_year - Report the bundled OEWS data year and release

Reference

  • list_common_soc_codes - SOC code mappings for federal IT/professional services
  • list_common_metros - Metro area MSA codes
  • get_data_status - The bundled release, its BLS source files with SHA-256 and publication dates, and the retrieval date

Data source

The bundled database is built by scripts/build_oews_db.py from the BLS OEWS flat files at download.bls.gov/pub/time.series/oe/: national, state, metropolitan and nonmetropolitan area, and national industry estimates for every occupation and all 17 OEWS datatypes, including the relative standard errors. data/manifest.json records each source file's URL, size, SHA-256, and BLS publication date. A weekly check reports when BLS publishes a new release, which ships as a new package version.

BLS.gov cannot vouch for the data or analyses derived from these data after the data have been retrieved from BLS.gov.

Installation

bash
uvx --refresh-package bls-oews-mcp --from bls-oews-mcp bls-oews-mcp

Configuration

Use the configuration below as the server definition and adapt its placement to your compatible MCP client. For practical requests using this source, see the prompt library.

json
{  "mcpServers": {    "bls-oews": {      "command": "uvx",      "args": ["--refresh-package", "bls-oews-mcp", "--from", "bls-oews-mcp", "bls-oews-mcp"]    }  }}

The --refresh-package flag tells uv to check PyPI for a newer release each time your client launches the server, so fixes and new OEWS releases arrive automatically; without it, uv keeps serving whatever version it first cached. It adds a moment of network time at startup, so raise your platform's MCP startup timeout if it enforces a short one.

On first use the server decompresses the bundled database (about 50 MB) into your user cache directory; set BLS_OEWS_DATA_DIR to put it elsewhere.

Restart the client and the tools appear.

Example prompts

  • "What's the national median salary for Software Developers (SOC 151252)?"
  • "Compare Systems Analyst wages in DC, Seattle, and Baltimore."
  • "Build IGCE wage benchmarks for Program Manager, Software Developer, and Help Desk at the DC metro area with a 2.0x burden factor."
  • "Is $195/hr reasonable for a Senior Software Developer? Show me the BLS market data."
  • "What do Information Security Analysts earn in Virginia vs nationally?"

Important: base wages, not burdened rates

BLS OEWS data represents employer-reported base wages (no fringe, overhead, G&A, or profit). To estimate fully burdened hourly rates for an IGCE, apply a burden multiplier:

  • 1.5x-1.7x: lean contractor
  • 1.8x-2.2x: mid-range professional services
  • 2.0x-2.5x: large contractor with clearance overhead
  • 2.5x-3.0x: high-overhead (SCIF, deployed)

The igce_wage_benchmark tool applies the multiplier automatically. OEWS wages are estimates for the release's May reference month, so escalate them to the period of performance; the tool's wage_period and _escalation_note say which month.

Data year

OEWS publishes about a year in arrears. The server answers from the bundled release, 2025 (May 2025 estimates, published May 15, 2026); other years raise a clear error pointing to the historical tables at bls.gov/oes/tables.htm. Omit the year argument in normal use, and call detect_latest_year or get_data_status to see the bundled release.

Companion tools

Use alongside gsa-calc-mcp (GSA CALC+ ceiling rates) for complete pricing analysis. BLS provides what the market pays; CALC+ provides what GSA contractors charge. Together they form the IGCE pricing toolkit.

License

MIT

來源:servers/bls-oews-mcp/readme.md,提交 7ff19f1

工具

0
SourceWeft 尚未在沙箱中啟動過該軟體包,因此其工具未知。

版本歷史

1
  1. v0.2.7最新Sep 16, 2026

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