How to Use the Five9 QM MCP in Pydantic AI

Q: Does Pydantic AI support the Five9 QM calibration tools?

Yes. Use listcalibrations to fetch the data. Your agent then validates the session structure against your defined types.

Ensure type-safe quality management in Pydantic AI with the Five9 QM MCP Server.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Five9 QM MCP to Pydantic AI

Create your Vinkius account to connect Five9 QM to Pydantic AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

GDPR Free for Subscribers

Setup Five9 QM with Pydantic AI

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Type-safe evaluations in Pydantic AI

Every response from `create_evaluation` is validated against your Pydantic models. If the server returns malformed data, your agent catches it instantly. Using `get_evaluation_form` provides the schema your agent needs to build valid submissions. It prevents runtime errors before they reach the Five9 database.

Precise interaction control for Pydantic AI

Your agent uses `get_qm_interaction` to fetch call metadata as a typed object. It verifies the record exists before initiating any further processing. By calling `get_recording_link`, the agent retrieves the audio path. Because the output is strictly typed, your agent handles the link without guessing the format.

Reliable data management with MCP Server

Running `list_qm_agents` returns a clean list of personnel. Your agent uses this to ensure it only evaluates authorized staff members. Use `list_evaluations` to pull a batch of records for audit. The agent checks the structure of each entry to maintain data integrity across your reports.

Setup guide

Set up Five9 QM MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "five9-qm-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to Five9 QM tools.",
)

result = await agent.run("List recent Five9 QM transactions")
print(result.output)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Five9 QM. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Five9 QM now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Five9 QM MCP in Pydantic AI

The server returns structured JSON which your agent validates against Pydantic models. This guarantees data correctness at every step.

Yes. Use `list_calibrations` to fetch the data. Your agent then validates the session structure against your defined types.

Yes. Because every response is validated, silent data corruption is impossible. You get an error if the API returns unexpected fields.

The server runs externally and provides a stable interface. Your agent remains decoupled from the internal Five9 API changes.

We use scoped tokens for all operations. The system only handles interaction metadata and evaluation forms, keeping your sensitive data locked down.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript

Mastra AI sdk-typescript

Start using the Five9 QM MCP today

We host it, we monitor it, we maintain it. You just paste one token.

Get started