How do I get a link to listen to a specific call recording?

You can use the 'get_recording_link' tool by providing the Interaction ID. The agent will return a secure, temporary URL that allows you to play back the audio file directly.

Can I see the structure of an evaluation form before submitting a score?

Yes! The 'get_evaluation_form' tool retrieves the full structure of any quality form, including questions and scoring logic, so you can ensure you have the right context for your evaluation.

Is there a way to track organization-wide quality trends?

Absolutely. Use the 'get_qm_summary' tool to retrieve high-level metrics and summary reports that highlight overall quality performance across your entire contact center.

Five9 QM MCP Server for Pydantic AI 12 tools — connect in under 2 minutes

Name: Five9 QM
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 12 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Five9 QM through the 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 Five9 QM "
            "(12 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Five9 QM?"
    )
    print(result.data)

asyncio.run(main())

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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 Five9 QM MCP Server

Connect your Five9 Quality Management (QM) account to any AI agent and automate your quality assurance workflows through the Model Context Protocol (MCP). Five9 QM (formerly Virtual Observer) is a powerful tool for monitoring and scoring agent performance across voice and digital channels. Now, you can manage evaluations and review interactions directly through natural conversation.

Pydantic AI validates every Five9 QM tool response against typed schemas, catching data inconsistencies at build time. Connect 12 tools through the 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

Evaluation Management — List all completed evaluations, fetch detailed scores and feedback, and submit new evaluations instantly.
Interaction Review — Access recorded voice and digital interactions available for quality review and retrieve their full metadata.
Recording Retrieval — Generate temporary, secure links to audio recordings for direct playback and analysis.
Form Inspection — List all active quality evaluation forms and fetch their specific question and scoring structures.
Calibration Monitoring — Track active and completed calibration sessions to ensure scoring consistency across your QA team.
Agent & User Discovery — List agents available for evaluation and manage QM system users for better team context.
High-level Reporting — Fetch QM summary metrics to understand organization-wide quality trends and performance.

The Five9 QM MCP Server exposes 12 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 Five9 QM to Pydantic AI via MCP

Follow these steps to integrate the Five9 QM 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 12 tools from Five9 QM with type-safe schemas

Why Use Pydantic AI with the Five9 QM MCP Server

Pydantic AI provides unique advantages when paired with Five9 QM 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 Five9 QM integration code

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

Dependency injection system cleanly separates your Five9 QM connection logic from agent behavior for testable, maintainable code

Five9 QM + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Five9 QM MCP Server delivers measurable value.

Type-safe data pipelines: query Five9 QM with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Five9 QM tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Five9 QM and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Five9 QM responses and write comprehensive agent tests

Five9 QM MCP Tools for Pydantic AI (12)

These 12 tools become available when you connect Five9 QM to Pydantic AI via MCP:

create_evaluation

Submit a new evaluation

get_evaluation

Get evaluation details

get_evaluation_form

Get form structure

get_qm_interaction

Get interaction metadata

get_qm_summary

Get QM summary report

get_recording_link

Get audio recording link

list_calibrations

List calibration sessions

list_evaluation_forms

List evaluation forms

list_evaluations

List agent evaluations

list_qm_agents

List evaluatable agents

list_qm_interactions

List recorded interactions

list_qm_users

List QM system users

Example Prompts for Five9 QM in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Five9 QM immediately.

"List the last 5 completed agent evaluations."

"Get the recording link for interaction 'int_12345'."

"Show me all available evaluation forms."

Troubleshooting Five9 QM MCP Server with Pydantic AI

Common issues when connecting Five9 QM to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Five9 QM + Pydantic AI FAQ

Common questions about integrating Five9 QM 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 Five9 QM MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.