Can I view payroll details?

Yes! Use `list_payrolls` to see all runs, then `get_payroll` for detailed breakdowns per employee.

Can I see employee benefits?

Yes! Use `list_benefits` with a company ID to see all configured benefit plans including health, dental, and retirement.

Can I list all employees?

Yes! Use `list_employees` with a company ID to get the full roster with names, departments, and roles.

Gusto MCP Server for AutoGen 10 tools — connect in under 2 minutes

Name: Gusto
Availability: InStock
Author: Vinkius

microsoft.github.io/autogen/docs/tools/mcp-tools

Built by Vinkius GDPR 10 Tools Framework

Microsoft AutoGen enables multi-agent conversations where agents negotiate, delegate, and execute tasks collaboratively. Add Gusto as an MCP tool provider through Vinkius and every agent in the group can access live data and take action.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.tools.mcp import McpWorkbench

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with McpWorkbench(
        server_params={"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"},
        transport="streamable_http",
    ) as workbench:
        tools = await workbench.list_tools()
        agent = AssistantAgent(
            name="gusto_agent",
            tools=tools,
            system_message=(
                "You help users with Gusto. "
                "10 tools available."
            ),
        )
        print(f"Agent ready with {len(tools)} tools")

asyncio.run(main())

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 Gusto MCP Server

Connect Gusto to any AI agent and streamline your entire HR and payroll operation.

AutoGen enables multi-agent conversations where agents negotiate, delegate, and collaboratively use Gusto tools. Connect 10 tools through Vinkius and assign role-based access. a data analyst queries while a reviewer validates, with optional human-in-the-loop approval for sensitive operations.

What you can do

Employee Management — List and view employee profiles with compensation details
Payroll Operations — View payroll runs with earnings, taxes, and deductions
Company Info — Access company details, EIN, and configuration
Benefits Administration — Browse health, dental, 401k, and other benefit plans
Time-Off Policies — View PTO, sick leave, and vacation accrual rates
Departments & Locations — Organizational structure and office locations

The Gusto MCP Server exposes 10 tools through the Vinkius. Connect it to AutoGen 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 Gusto to AutoGen via MCP

Follow these steps to integrate the Gusto MCP Server with AutoGen.

Install AutoGen

Run pip install "autogen-ext[mcp]"

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Integrate into workflow

Use the agent in your AutoGen multi-agent orchestration

Explore tools

The workbench discovers 10 tools from Gusto automatically

Why Use AutoGen with the Gusto MCP Server

AutoGen provides unique advantages when paired with Gusto through the Model Context Protocol.

Multi-agent conversations: multiple AutoGen agents discuss, delegate, and collaboratively use Gusto tools to solve complex tasks

Role-based architecture lets you assign Gusto tool access to specific agents. a data analyst queries while a reviewer validates

Human-in-the-loop support: agents can pause for human approval before executing sensitive Gusto tool calls

Code execution sandbox: AutoGen agents can write and run code that processes Gusto tool responses in an isolated environment

Gusto + AutoGen Use Cases

Practical scenarios where AutoGen combined with the Gusto MCP Server delivers measurable value.

Collaborative analysis: one agent queries Gusto while another validates results and a third generates the final report

Automated review pipelines: a researcher agent fetches data from Gusto, a critic agent evaluates quality, and a writer produces the output

Interactive planning: agents negotiate task allocation using Gusto data to make informed decisions about resource distribution

Code generation with live data: an AutoGen coder agent writes scripts that process Gusto responses in a sandboxed execution environment

Gusto MCP Tools for AutoGen (10)

These 10 tools become available when you connect Gusto to AutoGen via MCP:

get_company

Get company details

get_employee

Get employee details

get_payroll

Get payroll run details

list_benefits

) with enrollment info. List company benefits

list_companies

List managed companies

list_departments

List company departments

list_employees

List employees in a company

list_locations

List company locations

list_payrolls

List payroll runs

list_time_off_policies

List time-off policies

Example Prompts for Gusto in AutoGen

Ready-to-use prompts you can give your AutoGen agent to start working with Gusto immediately.

"Show all employees in the engineering department."

"Show me the last payroll run details."

"List all time-off policies."

Troubleshooting Gusto MCP Server with AutoGen

Common issues when connecting Gusto to AutoGen through the Vinkius, and how to resolve them.

McpWorkbench not found

Install: pip install "autogen-ext[mcp]"

Gusto + AutoGen FAQ

Common questions about integrating Gusto MCP Server with AutoGen.

How does AutoGen connect to MCP servers?

Create an MCP tool adapter and assign it to one or more agents in the group chat. AutoGen agents can then call Gusto tools during their conversation turns.

Can different agents have different MCP tool access?

Yes. AutoGen's role-based architecture lets you assign specific MCP tools to specific agents, so a querying agent has different capabilities than a reviewing agent.