How to Use the Airmeet MCP in CrewAI
Deploy autonomous event teams. Give your CrewAI agents full control over Airmeet scheduling and moderation.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Airmeet MCP to CrewAI
Create your Vinkius account to connect Airmeet 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.
Assign CrewAI agents to moderate
Running a live virtual summit requires constant monitoring. You can spin up a CrewAI team where a monitor agent continuously polls `list_questions`. It watches the audience feed for specific keywords or spam. When the monitor flags an issue, it passes the context to a moderator agent in shared memory. The moderator then alerts your human staff. This MCP Server turns passive dashboards into active, autonomous defense systems.
Delegate conference configuration
Stop manually typing out session schedules. Build a hierarchical CrewAI setup where a manager agent reads a text file of your conference agenda. The manager delegates tasks to a builder agent equipped with `create_event` and `create_session`. The builder agent executes the API calls while a QA agent verifies the output using `list_events`. You just pass the Vinkius URL directly into the `mcps` array of your agent configuration to get started.
Generate insights from Airmeet MCP
After the conference ends, your crew takes over the reporting pipeline. An analyst agent triggers `get_event_attendance` and `list_poll_responses`. It crunches the numbers to find the most engaging talks. Meanwhile, a distribution agent uses `get_session_recordings` to draft follow-up emails with the correct video links. Using `MCPServerHTTP` with a `tool_filter`, you restrict each agent strictly to the tools they need for their specific job.
Set up Airmeet MCP in CrewAI
Prerequisites
- Python 3.10+ installed
-
crewaipackage (pip install crewai) - Active Vinkius subscription with a valid endpoint token
- 1
Install CrewAI
Run
pip install crewaito install the framework. MCP support is built-in via themcpsparameter. - 2
Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the
mcpslist. 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
Crewwith your agent and tasks. Callcrew.kickoff()— the agent will automatically invoke Airmeet tools as needed.
from crewai import Agent, Task, Crew
agent = Agent(
role="Airmeet Analyst",
goal="Access and analyze Airmeet data via MCP.",
backstory="Expert analyst with direct Airmeet access.",
mcps=[
"https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
],
)
task = Task(
description="List recent Airmeet transactions",
agent=agent,
expected_output="A summary of recent activity",
)
crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result) Prerequisites
- Python 3.10+ installed
-
crewai+crewai-toolspackages - Active Vinkius subscription with a valid endpoint token
- 1
Install dependencies
Run
pip install crewai crewai-tools. TheMCPServerAdapterhandles lifecycle management and tool conversion. - 2
Connect with MCPServerAdapter
Use
MCPServerAdapteras a context manager withSseServerParameterspointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle. - 3
Assign tools and run
Pass the returned
mcp_toolsto your agent'stoolsparameter. The adapter converts MCP tools to nativeBaseToolobjects compatible with all CrewAI agents.
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="Airmeet Analyst",
goal="Access and analyze Airmeet data via MCP.",
backstory="Expert analyst with direct Airmeet access.",
tools=mcp_tools,
)
task = Task(
description="List recent Airmeet transactions",
agent=agent,
expected_output="A summary of recent activity",
)
crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Airmeet. 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 Airmeet MCP in CrewAI
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