How to Use the Fellow MCP in AutoGen

Q: How do I register this Fellow MCP Server with my AutoGen assistant?

You use the mcpservertools adapter to convert the Fellow MCP schema for AutoGen. Pass the resulting tool list to your AssistantAgent constructor so the agent can call listmeetings or createactionitem during conversations.

Q: How do AutoGen agents know who to assign a Fellow task to?

The agents run listusers to retrieve the workspace directory and check active emails. They discuss who has the bandwidth for the task before calling the tool to assign it.

Let your AutoGen agents debate project priorities and assign Fellow action items based on consensus.

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Connect Fellow MCP to AutoGen

Create your Vinkius account to connect Fellow to AutoGen 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 Fellow with AutoGen

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Debate Priorities and Log Action Items

The `create_action_item` tool records team tasks once your AutoGen agents reach a consensus on project priorities. A product manager agent proposes a task, a developer agent reviews the technical feasibility, and they execute this tool only after agreeing on the scope. This consensus-driven process stops agents from logging duplicate or unrealistic tasks in your workspace. You get highly accurate action items that actually reflect your team's real capacity and technical requirements.

Audit Meetings with AutoGen Agents

The `get_meeting` tool pulls detailed meeting records so your AutoGen agents can analyze alignment across teams. A QA agent and a security agent review the meeting notes to verify that compliance topics were addressed before a launch. If the agents find missing approvals, they flag the discrepancy in their conversation. This multi-agent review ensures no critical launch steps are forgotten during busy shipping cycles.

Run Collaborative Workspace Cleanups in AutoGen

The `list_action_items` tool lets your AutoGen agents collaborate on cleaning up stale tasks in your workspace. One agent identifies overdue items, while a coordinator agent checks user availability to reassign the work. They negotiate who is best suited for the remaining tasks based on current workloads. Once they agree, they use the MCP Server tools to update the assignments and due dates, keeping your workspace clean.

Setup guide

Set up Fellow MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Fellow tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Fellow_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Fellow data")
print(result.messages[-1].content)

Get your connection token →

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Fellow_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Fellow data")
    print(result.messages[-1].content)

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 Fellow. 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 Fellow MCP in AutoGen

You use the mcp_server_tools adapter to convert the Fellow MCP schema for AutoGen. Pass the resulting tool list to your AssistantAgent constructor so the agent can call `list_meetings` or `create_action_item` during conversations.

Yes, the agents debate the conflict within their conversation thread. Once they decide on the correct state, one agent calls `complete_action_item` or `create_action_item` to apply the final decision to your workspace.

The agents run `list_users` to retrieve the workspace directory and check active emails. They discuss who has the bandwidth for the task before calling the tool to assign it.

Yes, this setup works perfectly over standard input/output (stdio) transports. Your terminal-based AutoGen agents can query streams and notes without requiring complex network configurations.

We isolate every connection using secure V8 sandboxes on our MCP Server that handle your `list_streams` and `get_stream` requests. Your meeting stream metadata is processed in memory and never written to persistent logs, keeping your corporate structure private.

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