How to Use the Five9 QM MCP in CrewAI

Q: How do CrewAI agents access call recordings in Five9 QM?

Your agents invoke getrecordinglink to retrieve the audio URL for any call interaction. The crew's analysis agent can then process the audio or transcript to identify compliance violations.

Deploy a multi-agent team in CrewAI to audit call center interactions and calibrate evaluations autonomously.

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Connect Five9 QM MCP to CrewAI

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

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Setup Five9 QM with CrewAI

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Set up specialized QA agent crews

Your CrewAI auditor agent scans call lists using `list_qm_interactions` and passes the bad calls to a specialized coaching agent. The auditor and supervisor agents coordinate these specialized roles using shared memory, ensuring they do not duplicate work. This multi-agent setup coordinates Five9 QM audits autonomously, allowing one agent to analyze the call while another logs performance feedback.

Run autonomous calibration audits via MCP Server

Your CrewAI agents use `list_calibrations` to track scoring discrepancies across different human supervisors and automated grading models. The agents compare human-marked scorecards against automated baselines to pinpoint discrepancies in grading. Using this MCP Server, the crew flags inconsistent grading behaviors, ensuring your Five9 QM evaluation standards remain uniform across all active call center campaigns.

Generate automated supervisor summaries for management

Your reporting agent pulls high-level compliance metrics using `get_qm_summary` and formats them into a structured markdown report for CrewAI tasks. This process runs entirely without human intervention, pulling data directly from the call center API. The resulting summary highlights agent performance trends, letting your CrewAI system escalate systemic training issues directly to Five9 QM administrators.

Setup guide

Set up Five9 QM MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke Five9 QM tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Five9 QM Analyst",
    goal="Access and analyze Five9 QM data via MCP.",
    backstory="Expert analyst with direct Five9 QM access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Five9 QM transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="Five9 QM Analyst",
        goal="Access and analyze Five9 QM data via MCP.",
        backstory="Expert analyst with direct Five9 QM access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Five9 QM transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

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.

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Common questions about Five9 QM MCP in CrewAI

Your agents invoke `get_recording_link` to retrieve the audio URL for any call interaction. The crew's analysis agent can then process the audio or transcript to identify compliance violations.

Yes, you can define specialized agents for auditing, scoring, and reporting. These agents use tools like `create_evaluation` to log performance scores directly into the system.

The server supports stdio, SSE, and HTTP transports, making it easy to connect your multi-agent crew. You can configure the connection using the standard CrewAI server client initialization.

Your crew uses shared memory to partition interactions fetched via `list_qm_interactions`. This prevents agents from scoring the same customer call twice, optimizing your API usage.

All agent names, supervisor logins, and interaction logs retrieved via `list_qm_users` are encrypted in transit and purged immediately after the crew completes its task.

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