Timing MCP Server

The Timing MCP Server bridges the gap between AI assistants and the Timing time‑tracking platform. By exposing a rich set of tools that map directly to Timing’s API, the server allows developers and users to orchestrate time‑management workflows entirely through natural language or scripted prompts. This eliminates the need to manually navigate Timing’s web interface, enabling assistants like Claude or Cursor to create, update, and report on projects and time entries in real‑time.

At its core, the server solves a common pain point: seamless integration of time‑tracking data into conversational AI pipelines. Developers can ask an assistant to start a new task, pause it, or generate a weekly report, and the server translates those high‑level commands into precise API calls. The result is a fluid experience where AI can both consume and modify Timing data without exposing raw endpoints to end users. This capability is especially valuable for teams that rely on AI‑powered productivity tools, as it keeps time records accurate and up to date while reducing friction.

Key features of the Timing MCP Server include:

• Project management: List, retrieve details, create, and update projects with simple tool calls.
• Time entry control: Start, stop, list, and modify time entries directly from the assistant’s context.
• Reporting: Generate custom reports that combine time‑entry data with application usage insights, facilitating performance reviews and billing.
• Secure authentication: Uses an API key passed via environment variables, ensuring that only authorized assistants can interact with a user’s Timing account.

Typical use cases span from personal productivity to enterprise analytics. A freelancer can ask their AI assistant, “Start a new time entry for the client project,” and receive instant confirmation. A project manager might request, “Show me all projects that are over budget,” triggering the server to pull data and format it for quick decision‑making. In larger organizations, the reporting tool can be invoked to produce daily dashboards that feed into other AI‑driven analytics workflows.

Integration is straightforward for MCP‑aware clients. Once the server is running, developers add its configuration to their assistant’s settings (e.g., for Claude or for Cursor). The assistant then discovers the available tools and can invoke them via standard MCP calls. Because the server abstracts away HTTP details, developers can focus on crafting conversational flows rather than handling OAuth or rate‑limiting concerns.

The Timing MCP Server stands out by providing a domain‑specific toolkit that aligns closely with the most common actions users perform in Timing. Its clear, well‑documented tool set, combined with secure API key handling and ready integration points for popular AI assistants, makes it a powerful addition to any developer’s AI‑first workflow.