How to Use the Toggl Plan MCP in AutoGen

Q: Can I use the MCP Server for initial project setup with Toggl Plan and AutoGen?

Yes. Agents can first list existing projects using listworkspaceprojects and then decide whether a new task needs to be created via createtimelinetask.

Use AutoGen for multi-agent consensus on Toggl Plan tasks via MCP Server.

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Connect Toggl Plan MCP to AutoGen

Create your Vinkius account to connect Toggl Plan 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 Toggl Plan with AutoGen

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Project Status Consensus with the MCP Server

The `get_project_details` tool lets agents gather raw data on a project's scope. Different specialized agents can then debate which details are most critical, converging on a single summary. Similarly, listing all milestones via `list_milestones` allows one agent to present the timeline while another debates feasibility.

Task Management Debates with AutoGen

Agents can use `create_timeline_task` and then challenge each other on its parameters (workspace ID, project ID). This simulates a review process where multiple perspectives confirm the task's necessity. When using `update_timeline_task`, different agents negotiate the correct JSON payload before committing the change.

Listing and Auditing Workspaces

Agents can call tools like `list_workspace_projects` or `list_workspace_tags` to gather comprehensive lists of resources. These lists become inputs for a debate, determining which category is most relevant. The agents can use `list_timeline_tasks` output to audit the current workload against defined project scope.

Setup guide

Set up Toggl Plan 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 Toggl Plan 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="Toggl Plan_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Toggl Plan. 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 Toggl Plan MCP in AutoGen

AutoGen uses MCP tools as sources of truth. Agents call tools like `list_workspace_users` to gather data, then debate what that data means or what action needs to be taken.

The agents work toward consensus on project status. For instance, they might argue whether a task needs updating (`update_timeline_task`) or if the project details are already complete.

This MCP Server provides structured access to workspace metadata, including user lists, available projects, task identifiers, and tag names. It's all organizational structure data.

Yes. Agents can first list existing projects using `list_workspace_projects` and then decide whether a new task needs to be created via `create_timeline_task`.

The server touches user access lists, project IDs, and task details. All data is handled as structured metadata necessary for agent deliberation.

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