MCP server for HR and compensation data including salary benchmarks, job listings, company reviews, and labor market insights for AI agents.
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Scored across 2 tools
The two tools have clearly distinct purposes: one focuses on H1B visa salary data, the other on general salary data. Descriptions make the difference explicit, so an agent can easily select the correct tool.
Both tools follow a consistent 'search_' prefix pattern with clear, descriptive nouns (h1b_salaries, salaries). The naming convention is uniform and predictable.
With only 2 tools for a HR & compensation domain, the set feels thin. While each tool serves a specific purpose, additional tools (e.g., for benefits, cost-of-living, or industry breakdowns) would be expected for comprehensive coverage.
The tools cover general and visa salary data, but lack other common compensation-related queries such as experience-level filtering, benefits information, or historical trends. This creates notable gaps for thorough analysis.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
search_h1b_salaries3 fields changedInput schema / properties / company / descriptionAdded value: +"Company name or partial name (e.g. 'Google', 'Meta', 'Apple')"Input schema / properties / job_title / descriptionAdded value: +"Job title to search (e.g. 'Software Engineer', 'Data Scientist', 'Product Manager')"Input schema / properties / location / descriptionAdded value: +"Work location as city or state (e.g. 'San Francisco, CA', 'Seattle, WA', 'New York')"search_salaries2 fields changedInput schema / properties / job_title / descriptionAdded value: +"Job position or role (e.g. 'Senior Software Engineer', 'UX Designer', 'DevOps Engineer')"Input schema / properties / location / descriptionAdded value: +"Geographic location for salary lookup (e.g. 'San Francisco, CA', 'remote', 'United States')"search_h1b_salariessearch_salaries
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