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 OpenAI Agents SDK 12 tools — connect in under 2 minutes

Name: Five9 QM
Availability: InStock
Author: Vinkius

openai.github.io/openai-agents-python/mcp

Built by Vinkius GDPR 12 Tools SDK

The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Five9 QM through Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails. no manual schema definitions required.

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 agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp

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

        agent = Agent(
            name="Five9 QM Assistant",
            instructions=(
                "You help users interact with Five9 QM. "
                "You have access to 12 tools."
            ),
            mcp_servers=[mcp_server],
        )

        result = await Runner.run(
            agent, "List all available tools from Five9 QM"
        )
        print(result.final_output)

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 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.

The OpenAI Agents SDK auto-discovers all 12 tools from Five9 QM through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries Five9 QM, another analyzes results, and a third generates reports, all orchestrated through Vinkius.

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 OpenAI Agents SDK 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 OpenAI Agents SDK via MCP

Follow these steps to integrate the Five9 QM MCP Server with OpenAI Agents SDK.

Install the SDK

Run pip install openai-agents in your Python environment

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Run the script

Save the code above and run it: python agent.py

Explore tools

The agent will automatically discover 12 tools from Five9 QM

Why Use OpenAI Agents SDK with the Five9 QM MCP Server

OpenAI Agents SDK provides unique advantages when paired with Five9 QM through the Model Context Protocol.

Native MCP integration via `MCPServerSse`, pass the URL and the SDK auto-discovers all tools with full type safety

Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure

Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate

First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output

Five9 QM + OpenAI Agents SDK Use Cases

Practical scenarios where OpenAI Agents SDK combined with the Five9 QM MCP Server delivers measurable value.

Automated workflows: build agents that query Five9 QM, process the data, and trigger follow-up actions autonomously

Multi-agent orchestration: create specialist agents. one queries Five9 QM, another analyzes results, a third generates reports

Data enrichment pipelines: stream data through Five9 QM tools and transform it with OpenAI models in a single async loop

Customer support bots: agents query Five9 QM to resolve tickets, look up records, and update statuses without human intervention

Five9 QM MCP Tools for OpenAI Agents SDK (12)

These 12 tools become available when you connect Five9 QM to OpenAI Agents SDK 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 OpenAI Agents SDK

Ready-to-use prompts you can give your OpenAI Agents SDK 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 OpenAI Agents SDK

Common issues when connecting Five9 QM to OpenAI Agents SDK through the Vinkius, and how to resolve them.

MCPServerStreamableHttp not found

Ensure you have the latest version: pip install --upgrade openai-agents

Agent not calling tools

Make sure your prompt explicitly references the task the tools can help with.

Five9 QM + OpenAI Agents SDK FAQ

Common questions about integrating Five9 QM MCP Server with OpenAI Agents SDK.

How does the OpenAI Agents SDK connect to MCP?

Use MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.