How to Use the Toggl Plan MCP in CrewAI

Q: How do I gather project scope using Toggl Plan with CrewAI?

The crew runs gettimelineview, passing in the required start and end dates to pull a visual report. This gives all specialized agents the necessary data for analysis.

Q: What tools can I use to list available resources from Toggl Plan with CrewAI?

Agents run listworkspaceprojects, listworkspacemembers, and listworkspacetags to pull comprehensive lists. These lists provide the raw context needed for planning.

Q: If I need task details for Toggl Plan with CrewAI, what should my agent do?

The specialized agent runs gettaskdetails, passing in the specific timeline task identifier. This retrieves all activity and segment data for a thorough review.

Q: Is it possible to list all milestones using Toggl Plan with CrewAI?

Yes, the listmilestones tool makes it easy for your crew to pull a clean list of every milestone marker. It's perfect for project health checks.

Run multi-agent operations against Toggl Plan using CrewAI's specialized agents.

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Coordinate Timeline Changes with the MCP Server

The `create_milestone` tool lets a specialist agent drop a new milestone diamond onto the timeline. Another key function is `create_timeline_task`, where agents input names, start dates, and end dates to build out project segments. If the data gets messed up, an agent can use `delete_timeline_task`. Remember, that action is irreversible, so your moderator agent needs to confirm it first.

Gathering Project Context with Toggl Plan

The crew can build a full scope report by calling `get_timeline_view` with specific date ranges. It pulls the visual data needed for analysis. For lists, agents use `list_workspace_projects`, `list_workspace_members`, and `list_workspace_tags` to map out all available resources. Need just one task's history? The dedicated agent calls `get_task_details`.

Updating Plans with the MCP Server

When a project shifts, an agent uses `update_timeline_task`, passing in a structured JSON object to modify existing segments. This is crucial for dynamic planning. For checking what's up, `list_milestones` gives a clean list of all markers. You can also use `list_workspace_tags` if you need the latest categorization structure.

Setup guide

Set up Toggl Plan MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke Toggl Plan tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Toggl Plan Analyst",
    goal="Access and analyze Toggl Plan data via MCP.",
    backstory="Expert analyst with direct Toggl Plan access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Toggl Plan transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

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

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Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

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

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="Toggl Plan Analyst",
        goal="Access and analyze Toggl Plan data via MCP.",
        backstory="Expert analyst with direct Toggl Plan access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Toggl Plan transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

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

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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 CrewAI

The crew runs `get_timeline_view`, passing in the required start and end dates to pull a visual report. This gives all specialized agents the necessary data for analysis.

Agents run `list_workspace_projects`, `list_workspace_members`, and `list_workspace_tags` to pull comprehensive lists. These lists provide the raw context needed for planning.

The specialized agent runs `get_task_details`, passing in the specific timeline task identifier. This retrieves all activity and segment data for a thorough review.

This server handles project metadata, including names, associated tags, and team member lists. The agents read this information to build reports without accessing private user credentials.

Yes, the `list_milestones` tool makes it easy for your crew to pull a clean list of every milestone marker. It's perfect for project health checks.

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