How do I find my Client ID and Secret?

You must contact your Paylocity Account Manager or the Paylocity Web Services team to request API credentials. They will provide the Client ID and Client Secret for the WebLink API.

Where do I get the Company ID?

Your Company ID is the unique identifier for your organization in Paylocity, typically a 5 or 6 digit number used when logging into the Paylocity portal.

Can I see an employee's direct deposit setup?

Yes! Use the `get_employee_direct_deposit` tool with an Employee ID to retrieve the configured bank accounts and distribution settings.

Paylocity MCP Server for CrewAI 10 tools — connect in under 2 minutes

Name: Paylocity
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

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

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

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Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Paylocity Specialist",
    goal="Help users interact with Paylocity effectively",
    backstory=(
        "You are an expert at leveraging Paylocity 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 Paylocity "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 10 available tools "
        "and what they can do."
    ),
)

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

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* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Paylocity MCP Server

Connect your Paylocity account to any AI agent and take full control of your HR and payroll administration through natural conversation.

When paired with CrewAI, Paylocity becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Paylocity 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

Workforce Visibility — List all employees and retrieve detailed profiles, including contact info and job metadata.
Earnings & Deductions Tracking — Inspect specific earning codes and deduction setups for any employee.
Onboarding Oversight — List employees currently in the onboarding process to track hiring progress.
Payroll Auditing — Retrieve local tax configurations, direct deposit settings, and benefit setups to ensure compliance.
Custom Data Retrieval — Access custom fields defined in your Paylocity environment for specific reporting needs.

The Paylocity MCP Server exposes 10 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 Paylocity to CrewAI via MCP

Follow these steps to integrate the Paylocity 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 10 tools from Paylocity

Why Use CrewAI with the Paylocity MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Paylocity 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

Paylocity + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Paylocity MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Paylocity 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 Paylocity, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Paylocity 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 Paylocity against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Paylocity MCP Tools for CrewAI (10)

These 10 tools become available when you connect Paylocity to CrewAI via MCP:

get_employee

Get details for a specific employee

get_employee_benefit_setup

Get benefit configuration for an employee

get_employee_custom_fields

Get custom field values for an employee

get_employee_deductions

Get deduction details for an employee

get_employee_direct_deposit

Get direct deposit setup for an employee

get_employee_earnings

Get earning details for an employee

get_employee_emergency_contacts

Get emergency contacts for an employee

get_employee_local_taxes

Get local tax setup for an employee

list_employees

List all employees in the company

list_onboarding_employees

List employees currently in onboarding

Example Prompts for Paylocity in CrewAI

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

"List all employees in our company."

"Show me the earnings and deductions for employee 12345."

"Who is currently in the onboarding process?"

Troubleshooting Paylocity MCP Server with CrewAI

Common issues when connecting Paylocity 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.

Paylocity + CrewAI FAQ

Common questions about integrating Paylocity 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.