TimeTagger MCP Server

TimeTagger MCP Server – Seamless Time‑Tracking for AI Workflows

The TimeTagger MCP server bridges the gap between an AI assistant and a dedicated time‑tracking platform. It exposes a rich set of tools that let Claude or any MCP‑compatible assistant query, create, update, and manage time records directly from the chat interface. By converting TimeTagger’s REST API into intuitive, conversational commands, developers can embed time‑logging capabilities in productivity bots, reporting dashboards, or automated scheduling systems without writing custom API wrappers.

This server solves a common pain point: keeping track of work hours while maintaining conversational context. Rather than switching between a separate time‑tracking app and the AI, users can ask the assistant to “start a timer for client meeting” or “show me my hours spent on project X last week.” The assistant handles authentication, constructs the appropriate API calls, and returns results in natural language. For developers, this means less boilerplate code, tighter integration with existing workflows, and the ability to leverage TimeTagger’s advanced features—such as tag‑based summaries and hidden records—through simple tool calls.

Key capabilities include:

• Time range queries: Retrieve records for any start‑to‑end window, or fetch recent activity in the last N hours.
• Record lifecycle management: Create new entries, update descriptions or timestamps, and hide/delete records when needed.
• Timer control: Start and stop timers with a single command, enabling real‑time tracking without manual input.
• Tag analytics: Search records by tag and generate daily or weekly summaries of time spent per tag, supporting productivity analysis.
• Settings access: View and modify TimeTagger configuration directly from the assistant, ensuring consistency across environments.

Real‑world scenarios that benefit from this MCP include:

• Freelance and agency workflows – automatically logging billable hours while conversing with clients.
• Remote teams – generating sprint‑level time reports on demand during stand‑ups or retrospectives.
• Productivity coaching bots – providing instant feedback on how time is allocated across tasks or projects.
• Automated invoicing – feeding time records into billing systems without manual export.

Integration is straightforward: developers add the server to their MCP configuration, supply the API key and endpoint as environment variables, and then reference the provided tools in their prompt templates or action plans. Because each tool is a declarative function, the assistant can validate inputs, handle errors gracefully, and maintain conversational context. The result is a frictionless experience where time‑tracking becomes an invisible part of the dialogue, freeing users to focus on higher‑value tasks.