Harvest Natural Language Time Entry MCP Server

Harvest Natural Language Time Entry MCP Server

The Harvest MCP server transforms the way developers and teams capture work hours by turning free‑form text into structured time entries. Instead of navigating a web interface or filling out rigid forms, an AI assistant can interpret phrases like “2 hours on Project X doing development work today” or “I’m off sick tomorrow” and automatically create the corresponding entry in Harvest. This eliminates friction, reduces errors, and speeds up daily logging—especially valuable for distributed teams or freelancers who rely on conversational tools.

At its core, the server exposes a set of intuitive tools that map natural language to Harvest API calls. The log_time tool parses dates, durations, projects, and tasks from a sentence, applies timezone awareness, and handles special cases such as leave requests by substituting the configured standard work‑day hours. get_time_report lets users request summaries in plain English—“Show me last month’s hours by project” or “Get task breakdown for this week”—and the server returns a structured report with billable metrics. Additional helper tools (list_projects, list_tasks, list_entries) provide quick context for the assistant to reference when composing responses.

Key capabilities include:

• Natural language parsing powered by chrono‑node for dates and a custom grammar for durations and entities.
• Automatic project/task matching that reduces manual selection errors.
• Leave request handling, converting phrases like “I’m taking annual leave next week” into a full‑day entry.
• Timezone and configurable work‑day support, ensuring entries reflect the user’s local time and typical daily hours.
• Rich reporting that includes billable vs non‑billable breakdowns and supports multiple grouping dimensions (project, client, task, user).

Developers can integrate this server into any Claude‑based workflow by registering the MCP endpoint. Once connected, a conversational assistant can answer questions such as “How many hours did I bill for Project Y last quarter?” or “Add 3.5 hours of meetings to Project Z.” The assistant can then invoke log_time or get_time_report automatically, delivering a seamless experience that blends human language with precise accounting data.

In real‑world scenarios, the Harvest MCP server shines for agile teams needing instant time tracking during stand‑ups, contractors who log hours on the go, or HR staff generating leave summaries. By abstracting away API details and providing a natural interface, it empowers developers to build AI‑driven productivity tools that feel conversational while remaining fully compliant with Harvest’s data model.