
BLS OEWS
io.github.1102tools由 GitHub 账号 1102tools 发布v0.2.7更新于 Oct 24, 2026
BLS Occupational Employment and Wage Statistics market wages. 7 tools.
概览
基于随包附带的 BLS OEWS 数据,回答美国职业工资问题,包括都市区对比和 IGCE 工资基准。
- 可以做什么
- 从随包附带的只读数据库提供 BLS 职业就业与工资统计,因此回答在本地完成,并标注数据版本、发布日期、检索日期和来源文件。工具涵盖按 SOC 代码查询全国、州或都市区工资,跨都市区或跨职业对比,带负担率估算的 IGCE 工资基准,SOC 与都市区代码查询,以及数据状态报告。当 BLS 未发布某项数值时,会保留 BLS 脚注并建议替代指标。
- 适用场景
- 适合价格分析、IGCE 编制和劳动力市场研究,需要某职业或地区的市场工资数据而不想直接查询 BLS 时使用。也适合核对某个报价时薪是否与已发布的市场数据相符。
- 运行要求
- 作为 PyPI 包在桌面 MCP 客户端中本地运行(uvx bls-oews-mcp),仅支持桌面端。无需 API 密钥;可选的 BLS_API_KEY 环境变量用于 BLS v2 API。首次使用会把约 50 MB 的数据库解压到用户缓存目录,可用 BLS_OEWS_DATA_DIR 更改位置。建议的配置使用包刷新参数,会在启动时增加网络耗时。
安装
在 SourceWeft 中
- 打开 控制台中的 BLS OEWS,将其添加到工作区。
- 为需要使用其工具的对话启用该服务。
Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。
其他 MCP 客户端
参照 仓库 中的启动说明。
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 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 areascompare_occupations- Compare wages across multiple occupations in one location
Workflow
igce_wage_benchmark- Wage benchmarks with burdened rate estimates for IGCE developmentdetect_latest_year- Report the bundled OEWS data year and release
Reference
list_common_soc_codes- SOC code mappings for federal IT/professional serviceslist_common_metros- Metro area MSA codesget_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
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.
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
来源:servers/bls-oews-mcp/readme.md,提交 7ff19f1
工具
0版本历史
1- v0.2.7最新Sep 16, 2026
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