How to Use the ClickUp MCP in AutoGen

Q: Is ClickUp integration in AutoGen difficult to set up?

It's straightforward. Use the mcpservertools function to register the server, and the adapter automatically converts the tools for your agents to use.

Q: How do my AutoGen agents access ClickUp lists?

They call the listlists tool as part of their conversation loop. You can see the entire deliberation process in your terminal as they interact with your workspace.

Let your AutoGen agents debate and execute ClickUp task management.

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Connect ClickUp MCP to AutoGen

Create your Vinkius account to connect ClickUp 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 ClickUp with AutoGen

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Debate ClickUp tasks with AutoGen agents

Set up a security agent to check task permissions while a project agent drafts the `create_task` request. They discuss the details until they reach a consensus. This setup prevents impulsive changes to your workspace. The agents challenge each other's reasoning before committing any action to your board.

Automate ClickUp workflows with multi-agent consensus

Use `list_spaces` and `list_folders` to provide the agents with the full context of your project structure. They decide the best path forward based on your specific team requirements. Agents negotiate the priority of tasks. This moves your project management beyond simple scripts into actual decision-making systems.

Convert ClickUp schemas automatically

The McpToolAdapter handles the heavy lifting of mapping ClickUp API schemas to your agents. You don't need to write custom glue code to get them talking. Just pass the tool list to your AssistantAgent and let the framework handle the communication. It supports both stdio and HTTP transports for your specific infrastructure needs.

Setup guide

Set up ClickUp 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 ClickUp 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="ClickUp_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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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="ClickUp_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent ClickUp 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 ClickUp. 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 ClickUp MCP in AutoGen

Define multiple agents with specialized roles and provide them the ClickUp tools. The agents will then debate and execute tasks based on the instructions you provide.

Yes, by using a multi-agent setup, you can have one agent propose a change and another verify it against your team guidelines before executing the update.

It's straightforward. Use the mcp_server_tools function to register the server, and the adapter automatically converts the tools for your agents to use.

They call the `list_lists` tool as part of their conversation loop. You can see the entire deliberation process in your terminal as they interact with your workspace.

Your workspace remains isolated within a V8 sandbox during every agent interaction. No persistent storage of your task data occurs on our side, and all communication is encrypted.

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