How to Use the Agora MCP in CrewAI

Q: How does CrewAI handle Agora recording sequences?

Because agents share memory, one agent can run acquirecloudrecording and pass the resulting resource ID to another agent responsible for startcloudrecording.

Deploy a CrewAI agent team to autonomously monitor Agora sessions, track usage metrics, and manage cloud recordings.

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Connect Agora MCP to CrewAI

Create your Vinkius account to connect Agora 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 Agora with CrewAI

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Perplexity

Multi-agent session monitoring

Single agents get overwhelmed trying to watch multiple live streams at once. Splitting the workload across a specialized crew makes your infrastructure management far more reliable. You assign a Watcher agent to poll `list_active_calls` and `list_whiteboard_rooms` through this MCP Server. When it detects a high-traffic room, it passes the context to an Action agent that decides whether to alert the moderation team.

Autonomous recording operations

Managing long-running broadcasts requires constant babysitting. You can train a dedicated recording agent to handle the entire lifecycle without human intervention. The agent knows to run `acquire_cloud_recording` first. Once `start_cloud_recording` fires, it periodically checks the status with `query_cloud_recording`. When the scheduled end time hits, it executes `stop_cloud_recording` and logs the final file location.

CrewAI project administration via MCP Server

Tracking costs across dozens of applications is tedious work. A financial agent can take over this administrative burden completely. It pulls the full roster using `list_projects`, then iterates through each one with `get_usage_stats`. The agent compiles a daily report of minute consumption and flags any projects that are burning through their budget too fast.

Setup guide

Set up Agora 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 Agora tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

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

Pass your Vinkius MCP Server URL directly into the configuration array when defining your agent. The framework handles the connection and exposes the tools automatically.

You certainly can. Import the HTTP server module and use the filter parameter to ensure a junior agent only accesses `get_project_details` while a manager agent can `create_project`.

Because agents share memory, one agent can run `acquire_cloud_recording` and pass the resulting resource ID to another agent responsible for `start_cloud_recording`.

Yes. You can configure the transport layer to use SSE or Streamable HTTP, allowing your agents to process active call lists as they arrive from the server.

Vinkius processes everything in an ephemeral sandbox. Your active room lists and project metadata exist only during the execution window, guaranteeing complete isolation for your users.

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