How to Use the Aventri MCP in CrewAI

Q: How do I restrict Aventri tool usage in CrewAI?

Use the toolfilter option in the MCP server configuration. This lets you decide exactly which Aventri tools each agent in your crew can access.

Deploy autonomous crews to manage Aventri event operations and monitor registrations without human input.

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Connect Aventri MCP to CrewAI

Create your Vinkius account to connect Aventri 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 Aventri with CrewAI

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Autonomous Event Monitoring

Assign a crew member to watch your event status using `list_events` and `search_events`. The agent periodically checks for new registrants and reports back to the crew. This removes the need for manual status checks. Your crew stays updated on event capacity and registration trends throughout the day.

Collaborative Registration Management

Use a specialized agent to handle incoming registrations via `add_pre_load`. Another agent on the crew verifies the data using `get_contact` before finalizing the entry. This role-based approach keeps your data accurate. One agent acts while the other checks the work, creating an automated verification loop.

Proactive Speaker Coordination

Let your crew manage speaker logistics using `list_speakers` and `create_speaker`. The agents coordinate these tasks without you needing to touch the system. This keeps your speaker records current. The crew handles the tedious work of updating bios and checking session assignments as event details change.

Setup guide

Set up Aventri 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 Aventri tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

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

Pass the Aventri MCP server URL to the agent's mcps list. The crew will automatically discover and use the available tools to complete their tasks.

Yes. CrewAI provides shared memory for your agents. One agent can find a contact with `get_contact` and pass that info to another for further action.

Use the tool_filter option in the MCP server configuration. This lets you decide exactly which Aventri tools each agent in your crew can access.

It does. You can assign different tools to different levels of your crew, allowing managers to handle high-level tasks while workers execute specific API calls.

All contact records are treated as transient memory. The agents only process the specific attendee names and emails required to fulfill their current assigned goal.

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