How to Use the Asana MCP in AutoGen

Q: How do AutoGen agents share access to Asana tools?

You register the tools, such as listtasks, with the group chat manager. This allows any agent in the AutoGen conversation to request task lists when their role requires it.

Q: How do I handle tool execution errors in an AutoGen Asana group chat?

If an MCP tool like createtask fails due to missing fields, the error is returned to the chat. Your critic agent reads the error message and prompts the planner to provide the missing data.

Q: Can AutoGen agents search for tasks across multiple Asana workspaces?

Yes, an agent can call listworkspaces to identify target directories, then coordinate with other agents to run searchtasks across those workspaces in parallel.

Let your AutoGen agents debate project priorities and execute updates directly on your Asana boards.

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Connect Asana MCP to AutoGen

Create your Vinkius account to connect Asana 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 Asana with AutoGen

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Run multi-agent debates on Asana tasks

The `get_task` tool provides the raw ticket data that your AutoGen agents need to debate priority. One agent analyzes the description while another reviews the history via `list_stories` to negotiate the next action. Once they agree on a priority level, a coordinator agent calls `update_task` to commit the changes. This MCP Server ensures no single agent acts without consensus.

Coordinate cross-project planning with this MCP Server

Use `list_projects` to let a planning agent map out dependencies across different teams. The agent shares this project list with a resource allocator agent to identify scheduling bottlenecks. This collaborative review determines exactly where new tasks should go before the executor agent calls `create_task` to build them.

Automate ticket triage and routing

The `search_tasks` tool allows a triage agent to find unassigned tickets in your workspace. It then passes the details to a developer agent to match the task requirements with team skills. After a brief negotiation, the agents use `update_task` to assign the ticket and move it to the correct section.

Setup guide

Set up Asana 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 Asana 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="Asana_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Asana 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="Asana_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

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

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Common questions about Asana MCP in AutoGen

You register the tools, such as `list_tasks`, with the group chat manager. This allows any agent in the AutoGen conversation to request task lists when their role requires it.

Yes, you can set up a two-agent flow where the first agent uses `get_task` to check the status, and the second agent only calls `update_task` after the first one approves the changes.

If an MCP tool like `create_task` fails due to missing fields, the error is returned to the chat. Your critic agent reads the error message and prompts the planner to provide the missing data.

Yes, an agent can call `list_workspaces` to identify target directories, then coordinate with other agents to run `search_tasks` across those workspaces in parallel.

The server runs in an isolated V8 sandbox that handles authentication securely. Your user details from `get_me` and task descriptions are only transmitted directly to the official API endpoint.

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