MCP Toggl Server
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- AlicenseAqualityDmaintenanceEnables control of Toggl time tracking directly from LLMs like Claude or ChatGPT. Supports starting/stopping timers, viewing current and historical time entries, managing projects, and generating weekly summaries through natural language.813 npm3MIT
- AlicenseAqualityDmaintenanceEnables Claude to interact with Toggl Track for time tracking, including starting/stopping timers, viewing current entries, and summarizing time by project via natural language.720 npmMIT
- AlicenseAqualityDmaintenanceEnables AI assistants to manage Toggl Track time entries, projects, and workspaces through natural language, supporting CRUD operations and past date time slots.1311 npm2MIT
- AlicenseNot gradedqualityCmaintenanceEnables AI assistants to interact with the Toggl time tracking API to manage time entries, projects, and workspaces through natural language.22MIT
- AlicenseBqualityDmaintenanceEnables time tracking and project management through the Clockify API. Supports starting/stopping timers, logging time entries, managing projects and tasks, and generating reports with natural language commands.215 npmMIT
- FlicenseNot gradedqualityNot gradedmaintenanceEnables fetching and analyzing Toggl time tracking data with intelligent parsing of Fibery entity references from task descriptions. Features smart caching, user filtering, and aggregated reporting to help track time spent on specific projects and entities.-
TDQS
Scored across 15 tools
Every tool has a clearly distinct purpose with no ambiguity. Tools like toggl_start_timer and toggl_stop_timer handle timer control, while toggl_get_time_entries and toggl_get_current_entry focus on retrieving time data, and reporting tools like toggl_daily_report and toggl_weekly_report serve specific output formats. There is no overlap in functionality.
All tools follow a consistent verb_noun pattern with the 'toggl_' prefix, using snake_case throughout. Examples include toggl_list_workspaces, toggl_start_timer, and toggl_clear_cache, making the naming predictable and easy to understand.
With 15 tools, the count is well-scoped for a Toggl time-tracking server. It covers authentication, data listing, timer operations, reporting, and caching without being overwhelming, with each tool earning its place in the workflow.
The tool set provides strong coverage for core time-tracking operations, including CRUD-like actions (list, start/stop, get entries) and reporting. A minor gap is the lack of tools for updating or deleting time entries, which agents might need to work around, but overall, the surface is nearly complete for the domain.