# BLS Wages MCP MCP > The `query_bls` tool lets you pull official wage and employment statistics from the Bureau of Labor Statistics. You can get median or average earnings for specific professions, compare wages across different states, or track how pay rates change over time. It's essential for anyone doing deep labor market analysis. ## Overview - **Category:** human-resources - **Price:** Free - **Tags:** salary-benchmarking, wage-statistics, occupational-data, compensation, labor-market, public-api ## Description If figuring out exact compensation—say, what a financial analyst earns in New York versus Boston—is part of your job, this MCP is required. Instead of sifting through outdated PDFs and messy government websites, you talk to your agent, and it handles the complex data querying for you. You can get precise median pay ranges by mapping hundreds of distinct professions against dozens of states. This lets you build real salary benchmarks instantly. When you connect this MCP via Vinkius, you get access to a powerful dataset that allows immediate comparison across geography or job type. It's all about getting hard data on wage distributions and knowing exactly what the market pays right now. ## Tools ### query_bls This tool runs a generic query against the BLS dataset. You must provide explicit series IDs and parameters to retrieve historical median wage data. ## Prompt Examples **Prompt:** ``` What is the median salary for Software Developers in Texas versus California? ``` **Response:** ``` Software Developers in California enjoy a median wage upward of $150,000, whereas the median in Texas is closer to $120,000. ``` **Prompt:** ``` Tell me the hourly wage differences for Registered Nurses nationally. ``` **Response:** ``` Registered Nurses nationally see an average hourly boundary of roughly $42.80, with highs well past $60 in coastal markets. ``` **Prompt:** ``` Compare top 90th percentile to bottom 10th for Accountants. ``` **Response:** ``` Entry-level (10th percentile) Accountants run near $48,000 yearly, standing in stark contrast to the top executive counterparts (90th percentile) pushing toward $135,000+. ``` ## Capabilities ### Benchmark wages by location Compare median earnings for the same profession in two or more distinct states. ### Track wage history Pull time-series data to see how a specific job's average pay has changed over several years. ### Determine salary percentiles Calculate the full wage distribution, from entry-level (10th percentile) to top earners (90th percentile). ## Use Cases ### Comparing pay for relocation A company is considering moving its office from Miami to Atlanta. The agent uses `query_bls` to query the median wage difference for 'Project Managers' in both cities, showing a concrete cost-of-labor delta they need to present to leadership. ### Verifying job market claims A recruiter hears that tech wages are booming. They use `query_bls` to pull data on 'Software Developers' over the last decade, proving whether the growth is real or if it was a temporary spike. ### Analyzing career ladder pay An HR professional wants to see how much an entry-level accountant earns versus a VP-level accountant. They use `query_bls` to compare the 10th percentile vs. 90th percentile for 'Accountants' across multiple states. ### Assessing regional market value A national franchise is expanding and needs to know if their typical service worker salary will be viable in a new state. They run `query_bls` comparing the median wage for 'Service Workers' across five potential expansion states. ## Benefits - Stop guessing salaries. Use the `query_bls` tool to pull real, median earnings for any profession across multiple states in one go. - Benchmarking is faster than ever. Compare a registered nurse's hourly rate in Texas versus California instantly, giving you immediate competitive data points. - Track pay trends over time. See how the average wage for software engineers has grown or shrunk over the last five years by querying historical series data. - Understand salary spread. You can compare the 10th percentile (entry-level) wages to the 90th percentile (top executive) salaries in a single job title. - Requires specific parameters, but that precision is key. Because `query_bls` demands BLS Series IDs, you get highly reliable and structured outputs every time. ## How It Works The bottom line is you get accurate salary comparisons without having to write complex API calls or navigate multiple government databases. 1. You tell your agent which profession and what specific states you want to compare. 2. The MCP uses the `query_bls` tool to run a targeted, multi-variable query against the BLS dataset. 3. Your agent sends back structured data showing median pay, average pay, and sometimes percentile ranges for every location you asked about. ## Frequently Asked Questions **How reliable is OEWS compared to private job boards?** Extremely. OEWS pulls directly from true tax and payroll disclosures to the government, eliminating inflated self-reported figures typical on private job sites. **Is a Key required?** Only one single Key is required from the registration page. Simply plug it into the settings page and access the entire 20-year catalog of wage distribution profiles globally. **Why is wage data a unique server?** Because querying compensation brackets specific to states and detailed codes (like separating Senior vs Junior codes horizontally) takes specialized tool structures optimally tailored here. **What are the concurrent lookup limits when using the `query_bls` tool?** The MCP supports up to 50 simultaneous lookbacks for `query_bls`. This limit allows you to run large comparisons and gather multiple data points in one session without hitting immediate rate restrictions. **Does the `query_bls` tool require knowledge of specific BLS numerical codes?** Yes, `query_bls` is designed as a generic time-series query and requires explicit BLS Series IDs. However, you can describe what you need (e.g., 'Software Engineer wages') and let your agent identify the correct underlying ID for you. **If I run `query_bls` for a very niche combination, how does it handle missing wage records?** The tool is built to handle incomplete data gracefully. If no record exists for the specific occupation and state pair you query, `query_bls` returns null or an appropriate error message instead of failing. **Can I use `query_bls` to analyze historical wage trends?** Absolutely. Since this MCP functions as a generic time-series query, you can easily compare median wages for the same role across multiple years or quarters using `query_bls`. This is perfect for spotting long-term market shifts. **Is the compensation data retrieved by `query_bls` tied to individual employees?** No, this MCP only accesses aggregated governmental statistics from the Bureau of Labor Statistics. The data provided through `query_bls` represents median and average earnings for groups, never private or personal identifying information.