Timewarrior MCP Server

The Timewarrior‑MCP server bridges the gap between human‑centric time‑tracking workflows and AI‑driven productivity tools. By exposing TimeWarrior’s powerful command‑line interface through the Model Context Protocol, developers can give AI assistants direct access to a user’s time logs, project breakdowns, and activity summaries. This eliminates the need for manual data exports or cumbersome API wrappers, allowing conversational agents to answer questions like “How many hours did I spend on project X last week?” or “What was my most productive day this month?”

At its core, the server translates MCP resource calls into TimeWarrior queries. When an AI client requests a resource such as , the server runs the appropriate TimeWarrior commands, parses the output, and returns structured JSON that the assistant can embed in its responses. This seamless data flow means developers can build context‑aware prompts that reference real‑time work metrics without writing custom parsers or maintaining separate data pipelines.

Key capabilities include:

• Real‑time analytics – Fetch hourly, daily, or weekly summaries of tracked time across projects and tags.
• Event querying – Retrieve specific intervals or events, enabling AI to suggest scheduling adjustments or highlight recurring tasks.
• Custom prompt integration – Combine TimeWarrior data with pre‑defined prompts to generate insights, reports, or visual dashboards directly within the assistant.
• Sampling support – Use MCP’s sampling hooks to cache frequent queries, reducing latency for repetitive analytics.

Typical use cases span personal productivity coaches that advise on time‑management habits, project managers who need up‑to‑date resource allocations, and developers building AI‑augmented IDEs that can remind them of pending tasks or suggest optimal break times. Because the server operates over standard MCP endpoints, it fits naturally into existing AI workflows: a client simply declares a dependency on the and gains instant access to all tracked time data without additional authentication layers.

What sets this server apart is its minimal friction. TimeWarrior already stores data locally in a simple, portable format; the MCP wrapper adds no overhead beyond the server process itself. Developers can therefore prototype AI‑powered time‑tracking features in minutes, leveraging TimeWarrior’s mature ecosystem while enjoying the flexibility of Model Context Protocol’s modular architecture.