Can I create an action item and assign it to a team member?

Yes! Use `create_action_item` with the title, assignee email, and optional due date. You can also link it to a specific meeting.

How do I get the notes from a specific meeting?

Use `list_notes` with the meeting ID to get all notes linked to that meeting, or `get_note` with a specific note ID for full content.

Can I mark action items as completed via the AI agent?

Absolutely. Use `complete_action_item` with the action item ID to mark it as done.

INSTANT PLUG AND PLAY

Fellow MCP Server for CrewAIGive CrewAI instant access to 12 tools to Check Fellow Status, Complete Action Item, Create Action Item, and more

Name: Fellow
Availability: InStock
Author: Vinkius

Built by Vinkius GDPR 12 Tools Framework

Connect your CrewAI agents to Fellow through Vinkius, pass the Edge URL in the `mcps` parameter and every Fellow tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Use with Your AI Agent

Ask AI about this App Connector for CrewAI

Open in ChatGPT Open in Claude Open in Perplexity

The Fellow app connector for CrewAI is a standout in the Productivity category — giving your AI agent 12 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Fellow Specialist",
    goal="Help users interact with Fellow effectively",
    backstory=(
        "You are an expert at leveraging Fellow tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Fellow "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 12 available tools "
        "and what they can do."
    ),
)

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

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Fellow MCP Server

Connect your Fellow workspace to any AI agent and manage your entire meeting workflow through natural conversation.

When paired with CrewAI, Fellow becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Fellow tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

What you can do

Meetings — List and inspect meetings with titles, participants, dates, and agendas.
Notes — Access structured meeting notes and AI-generated summaries.
Action Items — Create, track, and complete action items with assignees and due dates.
Streams — Browse recurring meeting series and their schedules.
Users — List all workspace members and their roles.

The Fellow MCP Server exposes 12 tools through the Vinkius. Connect it to CrewAI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 12 Fellow tools available for CrewAI

When CrewAI connects to Fellow through Vinkius, your AI agent gets direct access to every tool listed below — spanning meeting-management, collaborative-agendas, action-items, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.

check_fellow_status

Verify Fellow API connectivity

complete_action_item

Mark an action item as completed

create_action_item

Optionally link it to a meeting, assign to a user by email, and set a due date. Create a new action item from a meeting

get_action_item

Get details of a specific action item

get_meeting

Get full details of a specific meeting

get_note

Get full content of a specific note

get_stream

Get details of a specific meeting stream

list_action_items

Optionally filter by status: "pending", "completed", or "archived". List action items from meetings

list_meetings

List recent meetings from Fellow

list_notes

Optionally filter by a specific meeting ID to get notes for that meeting only. List meeting notes

list_streams

List all meeting streams (recurring series)

list_users

List all users in the Fellow workspace

Connect Fellow to CrewAI via MCP

Follow these steps to wire Fellow into CrewAI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 12 tools from Fellow

Why Use CrewAI with the Fellow MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Fellow through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Fellow + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Fellow MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Fellow for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Fellow, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Fellow tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Fellow against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Example Prompts for Fellow in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with Fellow immediately.

"Show me my recent meetings in Fellow."

"Create an action item 'Send proposal to client' and assign it to sarah@team.com with a due date of May 10."

"List all pending action items."

Troubleshooting Fellow MCP Server with CrewAI

Common issues when connecting Fellow to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Fellow + CrewAI FAQ

Common questions about integrating Fellow MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.