How to Use the TrackingTime MCP in CrewAI

Q: Does MCP Server support creating new clients?

You use the createproject tool for this. The crew can execute this step as part of a larger process, ensuring every project is properly initialized with a record.

Run autonomous operations for TrackingTime using CrewAI's multi-agent framework.

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Connect TrackingTime MCP to CrewAI

Create your Vinkius account to connect TrackingTime to CrewAI 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 TrackingTime with CrewAI

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Autonomous Time Logging with MCP Server

You can build a research agent that needs to know how much time was spent. It runs the `list_time_entries` tool, and then an analysis agent interprets those logs. The whole process happens autonomously. This is ideal for large-scale reporting. Instead of manually fetching data, your crew executes the tools needed—like gathering entries via `list_time_entries`—and presents a unified finding.

Full Project Lifecycle Management with CrewAI

Need to onboard a new client? Have one agent use `create_project`, and another agent immediately uses `create_task` based on the project ID. The agents collaborate without human intervention. The crew can also check for existing resources using tools like `list_projects` or `list_customers`. This prevents accidental duplication in your operational data.

Team Resource Mapping with CrewAI

Use specialized agents to map out who's working on what. An agent can call `list_workspace_users` and pass that list to a moderator agent, which then cross-references it against the current tasks (`list_tasks`). This setup ensures that all operational actions respect team boundaries. It provides immediate visibility into resource allocation across multiple projects.

Setup guide

Set up TrackingTime 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 TrackingTime tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

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

Get your connection token →

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="TrackingTime Analyst",
        goal="Access and analyze TrackingTime data via MCP.",
        backstory="Expert analyst with direct TrackingTime access.",
        tools=mcp_tools,
    )

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

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

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 TrackingTime. 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 TrackingTime MCP in CrewAI

You pass the MCP URL to your agents, giving them access to tools like `start_timer` and `stop_timer`. This allows a specialized agent to automatically manage time tracking based on workflow triggers.

It handles core project and resource data. Specifically, the server exposes methods for managing tasks (`list_tasks`), projects (`list_projects`), and recording usage times (`add_time_entry`).

Yes. You can assign a dedicated agent to monitor the system. When a change is needed, that agent invokes `update_task`, modifying the record autonomously within your workflow.

You use the `create_project` tool for this. The crew can execute this step as part of a larger process, ensuring every project is properly initialized with a record.

You just give the agents access to all relevant tools. They can sequentially call `list_projects` followed by `list_customers`, gathering a comprehensive view of your operational landscape.

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