About BLS OEWS MCP
BLS OEWS MCP provides employment and wage statistics from a bundled BLS release for labor-market research, price analysis, and IGCE development. Its tools cover national, state, and metro data, with source details attached to results.
Key features
- 01Occupation wage statistics
- 02Compare wages by metro or occupation
- 03IGCE benchmarks with burden estimates
- 04SOC code and metro references
- 05Release status and source details
Use cases
- 01Check wages for a SOC occupation
- 02Compare pay across metro areas
- 03Build IGCE wage benchmarks
- 04Review the bundled release and sources
MCP support
Exposes BLS OEWS data through MCP tools for wage queries, comparisons, benchmarks, and reference information.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
uvx bls-oews-mcpBLS_API_KEYSecretOptional BLS API key from https://data.bls.gov/registrationEngine/ for v2 (500/day).Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEbls-oews-mcp
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 setup | Install | Install |
- 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
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.
{
"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
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