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Toggl Track mit Gemini verbinden — über MCP

Manage Toggl Track (time entries, projects, clients, tags, workspaces) from any AI agent. 9 tools, basic-auth with API token.

HCBy HelpCode teamUpdated 2 min read Open source on GitHub

No credit card · 7-day trial · Self-host alternative available

MCP connector

Toggl Track

Manage Toggl Track (time entries, projects, clients, tags, workspaces) from any AI agent. 9 tools, basic-auth with API token.

Tools

9

Region

INTL

Category

time-tracking

Authentication

Basic Auth

Required env vars

TOGGL_API_TOKEN
Install in one click on Cloud

7-day free trial · No credit card

  • 7-day free trial
    No credit card required
  • GDPR & SOC 2 ready
    EU data residency, audit logs
  • Open-source on GitHub
    Source-available BSL-1.1
  • Works with ChatGPT, Claude, Gemini
    Any MCP-compatible client

No install? Use cloud.anythingmcp.com directly.

Sign in, install the Toggl Track in one click, paste the credentials, mint an MCP API key — done. No Docker, no git clone, no local server to run.

Open Cloud

TL;DR

Manage Toggl Track (time entries, projects, clients, tags, workspaces) from any AI agent. 9 tools, basic-auth with API token.

💡 Keine Installation? Nutze cloud.anythingmcp.com direkt. Einloggen, Connectors → Toggl Track klicken, Zugangsdaten einfügen, MCP-API-Key erzeugen — fertig. Kein Docker, kein git clone, kein lokaler Server.

Toggl Track + Gemini

Manage Toggl Track (time entries, projects, clients, tags, workspaces) from any AI agent. 9 tools, basic-auth with API token.

Voraussetzungen

Die vollständige Setup-Anleitung ist in den Connector eingebaut (im Store sichtbar, wenn du den Connector auswählst). Benötigte Umgebungsvariablen für diesen Connector:

TOGGL_API_TOKEN

Schritt 1 — Zugangsdaten holen

This connector wraps the Toggl Track API v9 (api.track.toggl.com/api/v9).

Setup:

  1. Log into https://track.toggl.com → bottom-left avatar → Profile settings → scroll to API Token → reveal/copy.
  2. Set TOGGL_API_TOKEN.

Authentication: HTTP Basic, with API token as the username and the literal string api_token as the password: Authorization: Basic base64(TOKEN:api_token) The adapter sets this automatically via BASIC_AUTH (username=token, password=api_token). DO NOT pass real user/password — Toggl only accepts the token-pair.

…(continued in the in-app connector instructions)

Schritt 2 — Adapter installieren

git clone https://github.com/HelpCode-ai/anythingmcp.git
cd anythingmcp && docker compose up -d

Schritt 3 — Connector in Gemini hinzufügen

Gemini CLI liest MCP-Server aus ~/.gemini/settings.json (oder %APPDATA%\gemini\settings.json unter Windows). Hinzufügen:

{
  "mcpServers": {
    "anythingmcp": {
      "httpUrl": "https://cloud.anythingmcp.com/mcp",
      "headers": { "Authorization": "Bearer YOUR_MCP_API_KEY" }
    }
  }
}
  1. Hole deinen MCP API Key aus AnythingMCP → Profil → MCP API Keys → Neuer Key.
  2. Speichern und gemini neu starten.
  3. /mcp in Gemini CLI ausführen — Toggl Track sollte als verfügbar gelistet sein.
  4. Vertex AI Studio: https://cloud.anythingmcp.com/mcp im tools-Array der Anfrage mit demselben Bearer-Header übergeben.

Verfügbare Tools

ToolWhat it does
toggl_track_meGet the authenticated user including default workspace ID, all workspaces, default project/tag
toggl_track_list_workspacesList workspaces the user belongs to
toggl_track_list_clientsList clients in a workspace
toggl_track_list_projectsList projects in a workspace
toggl_track_get_current_entryReturn the currently running time entry (if any), else null
toggl_track_list_time_entriesList time entries for the current user
toggl_track_create_time_entryCreate a new time entry
toggl_track_stop_time_entryStop a running time entry
toggl_track_delete_time_entryDelete a time entry permanently

FAQ

Unterstützen Gemini 1.5 Pro oder 2.x MCP? Ja — Gemini CLI ≥ 0.4 und die Vertex AI Tools API akzeptieren MCP httpUrl-Connectors mit Bearer-Header.

Nächste Schritte

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