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toggl-mcp-server

MCP.Pizza Chef: taiseimiyaji

Toggl MCP Server is a Model Context Protocol server that integrates AI assistants with the Toggl time tracking API. It allows natural language interaction to create, update, delete, and retrieve time entries, projects, and workspace information. Supporting multiple platforms, it facilitates seamless AI-driven time management workflows within Toggl.

Use This MCP server To

Create and update Toggl time entries via natural language Retrieve current running time entry details Stop running Toggl time entries through AI commands Fetch workspace and project information from Toggl Filter and list time entries for reporting or review Integrate Toggl time tracking into AI-enhanced productivity tools

README

Toggl MCP Server

Read this in: English | 日本語

English

Overview

Toggl MCP Server is a Model Context Protocol (MCP) server that allows AI assistants to interact with the Toggl time tracking API. This enables AI assistants to manage time entries, projects, and workspaces in Toggl directly through natural language.

Features

  • Get time entries with filtering options
  • Create new time entries
  • Update existing time entries
  • Delete time entries
  • Get current running time entry
  • Stop running time entries
  • Get workspace information
  • Get projects in a workspace
  • Multi-platform support (linux/amd64, linux/arm64)

Usage

MCP Configuration

To connect an AI assistant to this server, configure the MCP connection in your .cursor/mcp.json file:

{
  "mcpServers": {
    "toggl-mcp": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "TOGGL_API_TOKEN",
        "lyricrime/toggl-mcp-server"
      ],
      "env": {
        "TOGGL_API_TOKEN": "your_toggl_api_token"
      }
    }
  }
}

Once configured, your AI assistant can interact with Toggl directly through natural language commands.

Environment Variables

  • TOGGL_API_TOKEN (required): Your Toggl API token for authentication

License

MIT License


日本語

概要

Toggl MCP Serverは、AIアシスタントがTogglのタイム・トラッキングAPIと対話できるようにするModel Context Protocol (MCP)サーバーです。これにより、AIアシスタントは自然言語を通じてTogglのタイムエントリー、プロジェクト、ワークスペースを直接管理できるようになります。

機能

  • フィルタリングオプション付きのタイムエントリー取得
  • 新規タイムエントリーの作成
  • 既存タイムエントリーの更新
  • タイムエントリーの削除
  • 現在実行中のタイムエントリーの取得
  • 実行中のタイムエントリーの停止
  • ワークスペース情報の取得
  • ワークスペース内のプロジェクト取得
  • マルチプラットフォームサポート(linux/amd64, linux/arm64)

使用方法

MCP設定

AIアシスタントをこのサーバーに接続するには、.cursor/mcp.jsonファイルにMCP接続を以下のように設定します:

{
  "mcpServers": {
    "toggl-mcp": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "TOGGL_API_TOKEN",
        "lyricrime/toggl-mcp-server"
      ],
      "env": {
        "TOGGL_API_TOKEN": "あなたのTogglAPIトークン"
      }
    }
  }
}

設定が完了すれば、AIアシスタントは自然言語コマンドを通じて直接Togglと対話できるようになります。

環境変数

  • TOGGL_API_TOKEN(必須):認証用のToggl APIトークン

ライセンス

MITライセンス

toggl-mcp-server FAQ

How do I authenticate the Toggl MCP Server?
You authenticate by providing your Toggl API token as an environment variable (TOGGL_API_TOKEN) when running the server.
Can the Toggl MCP Server handle multiple workspaces?
Yes, it supports fetching and managing projects and time entries across multiple Toggl workspaces.
What platforms does the Toggl MCP Server support?
It supports linux/amd64 and linux/arm64 platforms for flexible deployment.
How do I configure the Toggl MCP Server with an AI assistant?
Configure the MCP connection in your .cursor/mcp.json file with the appropriate command and environment variables.
Can I stop a running time entry using this server?
Yes, the server provides an API to stop currently running time entries via natural language commands.
Is it possible to filter time entries when retrieving them?
Yes, the server supports filtering options to retrieve specific time entries based on criteria.
Does the Toggl MCP Server support creating new time entries?
Yes, you can create new time entries through the server using natural language requests.
How does the Toggl MCP Server improve AI assistant workflows?
It enables direct, real-time interaction with Toggl, automating time tracking tasks without manual Toggl UI use.