How to Use the TrackingTime MCP in Mastra AI

Q: How does TrackingTime fit into Mastra AI workflows?

The MCP Server provides time management tools like starttimer and stoptimer. You can wrap these actions in a multi-step workflow that handles retries if the initial logging attempt fails.

Q: Can I automate task updates using TrackingTime and Mastra AI?

Yes. You can build a workflow that monitors tasks via listtasks. If status changes are needed, you trigger the updatetask tool within your complex, multi-step process.

Q: Does MCP Server handle listing all clients?

The listcustomers tool handles this. You can integrate this into a larger workflow to ensure that any new project you create (createproject) is linked to an existing client record.

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Automated Time Tracking Workflows for Mastra AI

Imagine a process that runs automatically: If the system detects an incomplete time log, it triggers a retry. The MCP Server exposes tools like `list_time_entries` and `add_time_entry`, allowing you to build these conditional steps. Mastra handles failure gracefully. It can execute a workflow—like checking projects via `list_projects`—and if one step fails, it automatically tries an alternative method or notifies the right admin.

Project and Task Management for Mastra AI

You need to build complex operational logic around project lifecycle. Use `create_project` and `list_projects` together in a sequence. The workflow can check if a required client exists by calling `list_customers` before proceeding. This allows you to enforce business rules—for instance, only letting users create tasks (`create_task`) within an active project.

Managing User and Team Data with Mastra AI

Building a robust system means knowing who's on the team. The MCP Server provides `list_workspace_users` to pull all team members into your workflow engine. You can then use this list to validate users attempting to log time. If you need to know what specific user profile to work with, the agent calls `get_user_profile`. These tools build reliable context for multi-step processes.

Setup guide

Set up TrackingTime MCP in Mastra AI

Prerequisites

Node.js 18+ and a TypeScript project
@mastra/mcp + @mastra/core packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run npm install @mastra/mcp @mastra/core plus your preferred model provider (e.g. @ai-sdk/openai).
2

Configure the MCPClient
Create an MCPClient with your Vinkius endpoint as a URL object. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and inject tools
Call mcpClient.listTools() and spread the result into your agent's tools object. All TrackingTime tools become native Mastra tools.
4

Run with any model
Swap openai("gpt-4o") for any AI SDK-compatible provider. Call agent.generate() and the agent routes tool calls through MCP automatically.

agent.ts

import { MCPClient } from "@mastra/mcp";
import { Agent } from "@mastra/core/agent";
import { openai } from "@ai-sdk/openai";

const mcpClient = new MCPClient({
  id: "trackingtime-mcp-client",
  servers: {
    "trackingtime-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

const agent = new Agent({
  name: "TrackingTime Agent",
  model: openai("gpt-4o"),
  instructions: "You have access to TrackingTime tools.",
  tools: {
    ...(await mcpClient.listTools()),
  },
});

const result = await agent.generate(
  "List recent TrackingTime transactions"
);
console.log(result.text);

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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 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 Mastra AI

The MCP Server provides time management tools like `start_timer` and `stop_timer`. You can wrap these actions in a multi-step workflow that handles retries if the initial logging attempt fails.

It touches time logs, project definitions, and user profiles. Specifically, it uses `list_time_entries`, `create_project`, and `get_user_profile` to manage your core operational data.

Yes. You can build a workflow that monitors tasks via `list_tasks`. If status changes are needed, you trigger the `update_task` tool within your complex, multi-step process.

The `list_customers` tool handles this. You can integrate this into a larger workflow to ensure that any new project you create (`create_project`) is linked to an existing client record.

Mastra handles this by allowing conditional branching. The workflow can check if the entry already exists (using `list_time_entries`) and, if so, skip or modify the operation instead of failing.

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