Can I check the total commission for a specific employee using the agent?

Yes! Use the `get_employee_details` tool or the `list_payout_statements` tool. Your agent will fetch the relevant data, including the total commission amount for the period.

How do I list all the processed payouts for my team?

Simply ask the agent to `list_commission_payouts`. It will retrieve the full history of processed payouts from your CaptivateIQ account, including dates and totals.

Does the integration allow creating a new payout manual adjustment?

The current toolset focuses on querying and monitoring (Read-Only) for data analysis and payroll extraction. Adjustments or changes to the calculation logic should be managed via the CaptivateIQ web platform.

CaptivateIQ MCP Server for Pydantic AI 8 tools — connect in under 2 minutes

Name: CaptivateIQ
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 8 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect CaptivateIQ through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

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 pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to CaptivateIQ "
            "(8 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in CaptivateIQ?"
    )
    print(result.data)

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

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 CaptivateIQ MCP Server

Connect your CaptivateIQ account to any AI agent and orchestrate your incentive compensation, commission tracking, and payroll integration workflows through natural conversation.

Pydantic AI validates every CaptivateIQ tool response against typed schemas, catching data inconsistencies at build time. Connect 8 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Payout Oversight — List and retrieve detailed metadata for all processed commission payouts across your organization.
Statement Management — Access individualized payout statements for employees to verify earnings and calculations.
Employee Coordination — List and retrieve detailed profiles for all employees, including their plan designations and hierarchy.
Workbook Monitoring — Access and list your calculation workbooks and worksheets to ensure transparency in your commission logic.
Dispute Tracking — Monitor and list commission inquiries or disputes directly from your workspace.
Financial Reporting — Retrieve core account and integration information straight from your workspace.

The CaptivateIQ MCP Server exposes 8 tools through the Vinkius. Connect it to Pydantic AI 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 CaptivateIQ to Pydantic AI via MCP

Follow these steps to integrate the CaptivateIQ MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 8 tools from CaptivateIQ with type-safe schemas

Why Use Pydantic AI with the CaptivateIQ MCP Server

Pydantic AI provides unique advantages when paired with CaptivateIQ through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your CaptivateIQ integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your CaptivateIQ connection logic from agent behavior for testable, maintainable code

CaptivateIQ + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the CaptivateIQ MCP Server delivers measurable value.

Type-safe data pipelines: query CaptivateIQ with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple CaptivateIQ tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query CaptivateIQ and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock CaptivateIQ responses and write comprehensive agent tests

CaptivateIQ MCP Tools for Pydantic AI (8)

These 8 tools become available when you connect CaptivateIQ to Pydantic AI via MCP:

get_account_status

Retrieve core account/integration information

get_employee_details

Get details of a specific employee

list_commission_inquiries

List commission disputes and inquiries (generic search)

list_commission_payouts

List all processed commission payouts

list_employees

List all employee records and plan designations

list_payout_statements

List individualized payout statements for employees

list_workbooks

List all calculation workbooks

list_worksheets

List all calculation worksheets

Example Prompts for CaptivateIQ in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with CaptivateIQ immediately.

"List all processed commission payouts in CaptivateIQ."

"Show the payout statement for employee John Doe."

"Which calculation workbooks are available in my account?"

Troubleshooting CaptivateIQ MCP Server with Pydantic AI

Common issues when connecting CaptivateIQ to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

CaptivateIQ + Pydantic AI FAQ

Common questions about integrating CaptivateIQ MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your CaptivateIQ MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.