How to Use the Mav MCP in CrewAI

Q: How do I configure the Mav MCP Server in CrewAI?

Pass your Vinkius endpoint URL directly into the mcps list when initializing your CrewAI agents. The framework automatically discovers and registers the available playbooks.

Q: How do I limit which CrewAI agents can access Mav?

Use the MCPServerHTTP class and define a toolfilter. This restricts access to the MCP SMS playbooks to only the specific agents you authorize.

Q: What python packages are required?

Run pip install crewai "crewaitools" to get the core framework and the necessary networking dependencies for external server connections.

Coordinate multi-agent teams to run autonomous SMS qualification playbooks in CrewAI.

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Connect Mav MCP to CrewAI

Create your Vinkius account to connect Mav 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 Mav with CrewAI

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Perplexity

Collaborative Lead Qualification with CrewAI

The Mav MCP Server connects your multi-agent teams directly to your outbound SMS qualification pipeline. Single agents struggle with complex sales funnels. CrewAI solves this by letting you build a team of specialized agents that work together. One agent drafts the SMS hook, while another triggers the Mav playbook to begin the conversation. This division of labor keeps your outbound campaigns highly targeted. The agents share memory, ensuring that follow-up texts reference previous interactions without repeating themselves.

Autonomous SMS Operations via MCP Server

Running outbound campaigns manually wastes hours of sales time. By connecting this MCP Server to CrewAI, your autonomous crew can scan incoming leads, verify opt-in status, and trigger Mav playbooks without human intervention. You configure the workflow once, and the agents handle the rest. They run in the background, qualifying leads at 2 AM so your account executives wake up to booked meetings.

Selective Tool Exposure for Crew Security

You don't always want every agent to have full access to your SMS gateway. CrewAI allows you to use `MCPServerHTTP` with a `tool_filter` to limit which agents can trigger Mav playbooks. This keeps your outbound campaigns safe from rogue agent actions. Your copywriter agent can draft messages, but only your dedicated dispatch agent can actually send them.

Setup guide

Set up Mav 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 Mav tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent Mav 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="Mav Analyst",
        goal="Access and analyze Mav data via MCP.",
        backstory="Expert analyst with direct Mav access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Mav 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 Mav. 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 Mav MCP in CrewAI

Pass your Vinkius endpoint URL directly into the `mcps` list when initializing your CrewAI agents. The framework automatically discovers and registers the available playbooks.

Yes, they can. CrewAI's shared memory allows different agents to trigger or monitor Mav playbooks while maintaining a single cohesive conversation history.

Use the `MCPServerHTTP` class and define a `tool_filter`. This restricts access to the MCP SMS playbooks to only the specific agents you authorize.

Run `pip install crewai "crewai[tools]"` to get the core framework and the necessary networking dependencies for external server connections.

Yes. All phone numbers and opt-in records are processed in a zero-trust, ephemeral V8 sandbox. We never store your contact lists or conversational histories on our infrastructure.

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