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Come collegare Toggl Track a Gemini — via 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.

💡 Niente installazione? Vai direttamente su cloud.anythingmcp.com. Accedi, clicca Connectors → Toggl Track, inserisci le credenziali, genera una MCP API key — fatto. Niente Docker, niente git clone, niente server locale.

Toggl Track + Gemini

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

Prerequisiti

Le istruzioni di setup complete sono incluse nel connettore stesso (visibili nello store quando lo selezioni). Le variabili d'ambiente richieste sono:

TOGGL_API_TOKEN

Step 1 — Ottieni le credenziali

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)

Step 2 — Installa l'adapter

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

Step 3 — Aggiungi il connettore in Gemini

Gemini CLI legge i server MCP da ~/.gemini/settings.json (o %APPDATA%\gemini\settings.json su Windows). Aggiungi:

{
  "mcpServers": {
    "anythingmcp": {
      "httpUrl": "https://cloud.anythingmcp.com/mcp",
      "headers": { "Authorization": "Bearer YOUR_MCP_API_KEY" }
    }
  }
}
  1. Ottieni la tua MCP API key da AnythingMCP → Profilo → MCP API Keys → Nuova Key.
  2. Salva il file e riavvia gemini.
  3. Esegui /mcp nella Gemini CLI — Toggl Track dovrebbe essere elencato come disponibile.
  4. Vertex AI Studio: passa https://cloud.anythingmcp.com/mcp nell'array tools della richiesta con lo stesso header Bearer.

Tool disponibili

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

Gemini 1.5 Pro o 2.x supportano MCP? Sì — Gemini CLI ≥ 0.4 e la Vertex AI tools API accettano connettori MCP httpUrl con header Bearer.

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