How to Use the MPU-Manager MCP in CrewAI

Q: How do I connect CrewAI to MPU-Manager?

Install the framework using pip install crewai "crewaitools". Pass your Vinkius endpoint URL directly into the mcps array parameter when defining your agent.

Q: Can I restrict which MPU-Manager tools a CrewAI agent can use?

Yes. Import MCPServerHTTP from crewai.mcp and configure a toolfilter. This lets you give one agent read-only access to schedules while granting another agent permission to create appointments.

Deploy autonomous production crews to manage your broadcast schedule using CrewAI.

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Connect MPU-Manager MCP to CrewAI

Create your Vinkius account to connect MPU-Manager 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 MPU-Manager with CrewAI

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Coordinate Agents with MPU-Manager

The `list_cases` tool feeds active production data directly into your CrewAI manager agent. This agent reads the daily broadcast schedule and delegates specific tracking tasks to subordinate agents. A specialized reporting agent then takes those case IDs and runs `list_reports` to compile a daily briefing. The agents share this context in memory, allowing them to collaborate without asking you for instructions.

Autonomous Crew Scheduling

Your logistics agent monitors availability by continuously polling `list_appointments`. When it detects a scheduling conflict for the camera team, it alerts the moderator agent. The moderator agent then executes `create_appointment` to book a backup crew. This hierarchical execution ensures production never stops due to a missed shift.

Filter MCP Server Tools by Role

You restrict access by applying a `tool_filter` on the `MCPServerHTTP` class. The scheduling agent only gets access to `get_appointment`, while the admin agent holds the keys to `create_case`. Before any agent takes action, a monitor agent can run `check_mpumanager_status` to ensure the system is online. If the check fails, the crew halts execution and waits for connectivity to return.

Setup guide

Set up MPU-Manager 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 MPU-Manager tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent MPU-Manager 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 →

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="MPU-Manager Analyst",
        goal="Access and analyze MPU-Manager data via MCP.",
        backstory="Expert analyst with direct MPU-Manager access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent MPU-Manager 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 MPU-Manager. 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 MPU-Manager MCP in CrewAI

Install the framework using `pip install crewai "crewai[tools]"`. Pass your Vinkius endpoint URL directly into the `mcps` array parameter when defining your agent.

Yes. Import `MCPServerHTTP` from `crewai.mcp` and configure a `tool_filter`. This lets you give one agent read-only access to schedules while granting another agent permission to create appointments.

Agents share context through CrewAI memory. If one agent pulls records using `get_client`, another agent can read that data to inform its scheduling decisions later in the pipeline.

Your agents will fail the current tool call. You should configure a monitor agent to run `check_mpumanager_status` before starting complex hierarchical workflows.

The agents read internal crew assignments, asset tracking IDs, and broadcast schedules. Vinkius secures this data by executing every tool call inside an ephemeral sandbox. The environment requires a single endpoint token and leaves zero trace after the task completes.

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