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How to Use the Fellow MCP in CrewAI

Coordinate multi-agent teams using CrewAI to manage your meeting agendas and tasks via the Fellow MCP Server.

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Works with every AI agent you already use

…and any MCP-compatible client

Fellow MCP on Cursor AI Code Editor MCP Client Fellow MCP on Claude Desktop App MCP Integration Fellow MCP on OpenAI Agents SDK MCP Compatible Fellow MCP on Visual Studio Code MCP Extension Client Fellow MCP on GitHub Copilot AI Agent MCP Integration Fellow MCP on Google Gemini AI MCP Integration Fellow MCP on Lovable AI Development MCP Client Fellow MCP on Mistral AI Agents MCP Compatible Fellow MCP on Amazon AWS Bedrock MCP Support
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CrewAI

Connect Fellow MCP to CrewAI

Create your Vinkius account to connect Fellow 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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Run autonomous workspace audits with CrewAI

`list_meetings` lets your CrewAI manager agent scan recent calendar events to coordinate downstream tasks. The manager agent delegates specific meetings to researcher agents for deep analysis. A researcher agent then calls `get_meeting` to extract the full agenda. This collaborative approach ensures your entire meeting history is parsed without manual overhead.

Resolve workspace tasks using an MCP Server

`list_action_items` provides your specialized CrewAI agents with a complete list of outstanding workspace tasks. One agent can filter for pending items while another prepares updates. Once a task is verified, the action agent executes `complete_action_item` to close the loop. The MCP Server ensures all tasks stay synced across agents.

Generate meeting agendas with specialized CrewAI teams

`create_action_item` allows your execution agent to assign new tasks directly to team members by email. The agent coordinates with a supervisor agent to ensure the due dates align with project milestones. By checking `list_users`, the crew matches emails to active workspace members before creating any items. This prevents broken assignments and keeps your team directories clean.

Setup guide

Set up Fellow MCP in CrewAI

Prerequisites

  • Python 3.10+ installed
  • crewai package (pip install crewai)
  • Active Vinkius subscription with a valid endpoint token
  1. 1

    Install CrewAI

    Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.

  2. 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. 3

    Kick off your crew

    Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke Fellow tools as needed.

crew.py
from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent Fellow transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Fellow MCP in CrewAI

Pass your Vinkius HTTP endpoint URL directly into the agent's `mcps` list during initialization. This instantly exposes tools like `get_note` and `list_streams` to that specific agent.
CrewAI agents can read notes using `get_note` and list them via `list_notes`. They use these details to trigger other tasks, though they must rely on action item tools to make modifications.
Your crew's coordinator agent calls `list_users` to find the correct team member's email. It then passes that email to `create_action_item` to assign the task during workflow execution.
Yes, you can use `MCPServerHTTP` with a `tool_filter` to only expose safe tools like `list_meetings` to your agents. This prevents autonomous agents from accidentally running write operations like `complete_action_item`.
Your raw meeting note text fetched via `get_note` is held in ephemeral memory during the crew's MCP execution cycle. It is never persisted on Vinkius disks, ensuring your internal operational data remains private.

Start using the Fellow MCP today

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