DeskTime MCP Server for Mastra AIGive Mastra AI instant access to 12 tools to Create New Task, Create Project, Get Company Info, and more
Mastra AI is a TypeScript-native agent framework built for modern web stacks. Connect DeskTime through Vinkius and Mastra agents discover all tools automatically. type-safe, streaming-ready, and deployable anywhere Node.js runs.
Ask AI about this App Connector for Mastra AI
The DeskTime app connector for Mastra AI is a standout in the Productivity category — giving your AI agent 12 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
import { Agent } from "@mastra/core/agent";
import { createMCPClient } from "@mastra/mcp";
import { openai } from "@ai-sdk/openai";
async function main() {
// Your Vinkius token. get it at cloud.vinkius.com
const mcpClient = await createMCPClient({
servers: {
"desktime": {
url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
},
},
});
const tools = await mcpClient.getTools();
const agent = new Agent({
name: "DeskTime Agent",
instructions:
"You help users interact with DeskTime " +
"using 12 tools.",
model: openai("gpt-4o"),
tools,
});
const result = await agent.generate(
"What can I do with DeskTime?"
);
console.log(result.text);
}
main();
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About DeskTime MCP Server
Connect your DeskTime account to any AI agent and take full control of your workforce management and productivity tracking workflows through natural conversation.
Mastra's agent abstraction provides a clean separation between LLM logic and DeskTime tool infrastructure. Connect 12 tools through Vinkius and use Mastra's built-in workflow engine to chain tool calls with conditional logic, retries, and parallel execution. deployable to any Node.js host in one command.
What you can do
- Project & Task Orchestration — List and manage time-tracking projects and individual tasks programmatically to maintain a high-fidelity record of work distribution
- Team Visibility — Monitor real-time staff activity, including who is currently online and tracking time, to coordinate team availability and throughput
- Productivity Intelligence — Access comprehensive productivity reports and performance metrics for individual employees or the entire company directly through your agent
- Workflow Automation — Programmatically create new projects, assign tasks, and mark work as completed to streamline your project management cycle
- Administrative Oversight — Retrieve detailed company metadata and employee directories to maintain a perfectly coordinated workforce ecosystem
The DeskTime MCP Server exposes 12 tools through the Vinkius. Connect it to Mastra AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 12 DeskTime tools available for Mastra AI
When Mastra AI connects to DeskTime through Vinkius, your AI agent gets direct access to every tool listed below — spanning time-tracking, workforce-management, productivity-analytics, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Add task to project
Add new project
Get company details
Check employee stats
Check company performance
Get project info
List company employees
Check who is working
List tasks in project
List DeskTime projects
Complete a task
Delete a project
Connect DeskTime to Mastra AI via MCP
Follow these steps to wire DeskTime into Mastra AI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
npm install @mastra/core @mastra/mcp @ai-sdk/openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.ts and run with npx tsx agent.tsExplore tools
Why Use Mastra AI with the DeskTime MCP Server
Mastra AI provides unique advantages when paired with DeskTime through the Model Context Protocol.
Mastra's agent abstraction provides a clean separation between LLM logic and tool infrastructure. add DeskTime without touching business code
Built-in workflow engine chains MCP tool calls with conditional logic, retries, and parallel execution for complex automation
TypeScript-native: full type inference for every DeskTime tool response with IDE autocomplete and compile-time checks
One-command deployment to any Node.js host. Vercel, Railway, Fly.io, or your own infrastructure
DeskTime + Mastra AI Use Cases
Practical scenarios where Mastra AI combined with the DeskTime MCP Server delivers measurable value.
Automated workflows: build multi-step agents that query DeskTime, process results, and trigger downstream actions in a typed pipeline
SaaS integrations: embed DeskTime as a first-class tool in your product's AI features with Mastra's clean agent API
Background jobs: schedule Mastra agents to query DeskTime on a cron and store results in your database automatically
Multi-agent systems: create specialist agents that collaborate using DeskTime tools alongside other MCP servers
Example Prompts for DeskTime in Mastra AI
Ready-to-use prompts you can give your Mastra AI agent to start working with DeskTime immediately.
"Show me a list of all employees currently tracking time."
"Check the productivity report for 'last_week'."
"Create a new task 'Review MCP API' in project ID '123'."
Troubleshooting DeskTime MCP Server with Mastra AI
Common issues when connecting DeskTime to Mastra AI through the Vinkius, and how to resolve them.
createMCPClient not exported
npm install @mastra/mcpDeskTime + Mastra AI FAQ
Common questions about integrating DeskTime MCP Server with Mastra AI.
How does Mastra AI connect to MCP servers?
MCPClient with the server URL and pass it to your agent. Mastra discovers all tools and makes them available with full TypeScript types.