How do I find my Salary.com API Key?

Log in to your [**Salary.com Developer portal**](https://developers.salary.com/), and you will find your API Key under the 'API Settings' or 'My Keys' section. Copy and paste it below.

Does the agent support local US data?

Yes. Salary.com provides high-density salary data across the entire United States, categorized by city and state.

Can the agent show job descriptions?

Yes. The `search_jobs` and `get_job_details` tools retrieve comprehensive job metadata, including responsibilities and required qualifications.

Salary.com API MCP Server for CrewAI 6 tools — connect in under 2 minutes

Name: Salary.com API
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 6 Tools Framework

Connect your CrewAI agents to Salary.com API through the Vinkius — pass the Edge URL in the `mcps` parameter and every Salary.com API tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Salary.com API Specialist",
    goal="Help users interact with Salary.com API effectively",
    backstory=(
        "You are an expert at leveraging Salary.com API tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token — get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Salary.com API "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 6 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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About Salary.com API MCP Server

Empower your AI agent to orchestrate your entire compensation research and career auditing workflow with Salary.com, the authoritative source for salary data. By connecting the Salary.com API to your agent, you transform complex benchmark lookups into a natural conversation. Your agent can instantly retrieve salary ranges for thousands of job titles, audit market trends, and search for open positions without you ever touching a technical portal. Whether you are managing payroll budgets or planning your next career move, your agent acts as a real-time compensation analyst, ensuring your data is always grounded in verified, high-quality market records.

When paired with CrewAI, Salary.com API becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Salary.com API tools autonomously — one agent queries data, another analyzes results, a third compiles reports — all orchestrated through the Vinkius with zero configuration overhead.

What you can do

Compensation Auditing — Retrieve high-resolution salary benchmarks for any job title and location, including base salary and percentile metadata.
Job Oversight — Search for open job positions and retrieve detailed descriptions and requirements to maintain a clear view of the market.
Trend Intelligence — Query salary market trends to understand the trajectory of compensation for specific roles instantly.
Career Discovery — List all available job categories in the Salary.com catalog to identify relevant paths for your research.
Operational Monitoring — Check API status to ensure your compensation research workflow is always operational.

The Salary.com API MCP Server exposes 6 tools through the Vinkius. Connect it to CrewAI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Salary.com API to CrewAI via MCP

Follow these steps to integrate the Salary.com API MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py — CrewAI auto-discovers 6 tools from Salary.com API

Why Use CrewAI with the Salary.com API MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Salary.com API through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles — one agent researches, another analyzes, a third generates reports — each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass the Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Salary.com API + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Salary.com API MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Salary.com API for raw data, then a second analyst agent cross-references findings and flags anomalies — all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Salary.com API, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Salary.com API tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Salary.com API against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Salary.com API MCP Tools for CrewAI (6)

These 6 tools become available when you connect Salary.com API to CrewAI via MCP:

check_api_status

com API is operational. Check if the Salary.com API is operational

get_job_details

Get full details for a specific job ID

get_salary_benchmark

Get salary benchmarks for a job title and location

get_salary_market_trends

Get market salary trends for a specific job title

list_job_categories

List all available job categories

search_jobs

Search for open jobs by keyword and location

Example Prompts for Salary.com API in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with Salary.com API immediately.

"What is the average salary for a 'Product Manager' in 'Austin, TX' using Salary.com?"

"Find open 'Software Engineer' jobs in 'San Francisco'."

"Show salary trends for 'Data Scientist' roles."

Troubleshooting Salary.com API MCP Server with CrewAI

Common issues when connecting Salary.com API to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts — check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

The Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Salary.com API + CrewAI FAQ

Common questions about integrating Salary.com API MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily — when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.