HR & Compensation MCP Server

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A".

If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows.

A Model Context Protocol server that gives AI agents compensation data — salary benchmarks and H-1B disclosed wages — as callable tools. For HR, recruiting and market-research agents.

- search_h1b_salaries— H-1B disclosed salary records.
- search_salaries— Salary data by role and location.

🔌 Connect (Claude Desktop / Cursor / n8n / OpenAI Agents SDK)

Add this MCP server to your client config:

{ "mcpServers": { "hr-compensation": { "url": "https://nexgendata--hr-compensation-mcp-server.apify.actor/mcp" } } }

Compare software-engineer salaries in Seattle against H-1B disclosed wages.

Pricing:$0.02 per tool call (Pay-Per-Event). Runs in Standby mode.

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You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '<YOUR_API_TOKEN>' with your token const client = new ApifyClient({ token: '<YOUR_API_TOKEN>', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("nexgendata/hr-compensation-mcp-server").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '<YOUR_API_TOKEN>' with your token. client = ApifyClient("<YOUR_API_TOKEN>") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("nexgendata/hr-compensation-mcp-server").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}") for item in client.dataset(run.default_dataset_id).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

echo '{}' | apify call nexgendata/hr-compensation-mcp-server --silent --output-dataset

{ "mcpServers": { "apify": { "type": "http", "url": "https://mcp.apify.com/?tools=fetch-actor-details,nexgendata/hr-compensation-mcp-server" } } }

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Query records of Korean independence activists from the Ministry of Patriots and Veterans Affairs.

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