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Start a free trial on cloud.anythingmcp.com, add the Clockify in one click, then point your AI client (Claude, ChatGPT, Copilot or Cursor) at the generated MCP endpoint. No Docker, no git clone, zero engineering experience required.
Summary
Manage Clockify (time tracking, projects, tasks, clients, tags, workspace users, reports) from any AI agent. 18 tools, X-Api-Key auth.
Try asking
Example prompts for Clockify
Click any prompt to copy it. Paste into Claude, ChatGPT, Cursor, Gemini, Copilot or OpenClaw to run it against this connector.
Claude is AI and can make mistakes. Please double-check responses.
💡 No install? Use cloud.anythingmcp.com directly. Sign in, click Connectors → Clockify, paste your credentials, mint an MCP API key — done. No Docker, no
git clone, no local server.
Clockify + Gemini
Manage Clockify (time tracking, projects, tasks, clients, tags, workspace users, reports) from any AI agent. 18 tools, X-Api-Key auth.
Prerequisites
See the full setup instructions baked into the connector (visible in the in-app store when you select the connector). The required environment variables for this connector are:
CLOCKIFY_API_KEY
Step 1 — Get credentials
This connector wraps the Clockify REST API v1 (api.clockify.me/api/v1).
Setup:
- Sign in to https://clockify.me → bottom-left avatar → Preferences → Advanced → API → Generate API key.
- Set
CLOCKIFY_API_KEY.
Authentication: X-Api-Key: ${CLOCKIFY_API_KEY} on every request.
Workspace IDs: Clockify is workspace-scoped. Use clockify_get_user first — its response contains defaultWorkspace and activeWorkspace. List workspaces with clockify_list_workspaces.
…(continued in the in-app connector instructions)
Step 2 — Install the adapter
curl -fsSL https://raw.githubusercontent.com/HelpCode-ai/anythingmcp/main/docker-compose.quickstart.yml -o docker-compose.yml
printf 'JWT_SECRET=%s\nENCRYPTION_KEY=%s\n' "$(openssl rand -hex 32)" "$(openssl rand -hex 32)" > .env
docker compose up -d
Step 3 — Add the connector in Gemini
Your server URL: in AnythingMCP, open MCP Servers → the server this connector is on, and copy its URL (
https://cloud.anythingmcp.com/mcp/…). Use it wherever this guide showsYOUR_SERVER_ID.
Gemini CLI reads MCP servers from ~/.gemini/settings.json (or %APPDATA%\gemini\settings.json on Windows). Add:
{
"mcpServers": {
"anythingmcp": {
"httpUrl": "https://cloud.anythingmcp.com/mcp/YOUR_SERVER_ID",
"headers": { "X-API-Key": "YOUR_MCP_API_KEY" }
}
}
}
- Get your MCP API key from AnythingMCP → MCP Servers → your server → API keys.
- Save the file and restart
gemini. - Run
/mcpinside the Gemini CLI —Clockifyshould be listed as available. - Vertex AI Studio: pass
https://cloud.anythingmcp.com/mcp/YOUR_SERVER_IDto thetoolsarray of your request with the sameX-API-Keyheader.
Available tools
| Tool | What it does |
|---|---|
clockify_get_user | Return the authenticated user: id, email, name, activeWorkspace, defaultWorkspace, profile picture URL |
clockify_list_workspaces | List workspaces the user belongs to |
clockify_list_workspace_users | List all users (members) of a workspace |
clockify_find_tasks | List tasks within a project |
clockify_add_task | Add a task to a project |
clockify_add_project | Create a project in a workspace |
clockify_add_client | Create a client in a workspace |
clockify_add_tag | Create a tag in a workspace |
clockify_list_clients | List clients in a workspace |
clockify_list_projects | List projects in a workspace |
clockify_list_tags | List tags in a workspace |
clockify_list_time_entries | List a user's time entries in a workspace |
clockify_start_time_entry | Start a new time entry |
clockify_stop_current_entry | Stop the currently running time entry for a user |
clockify_update_time_entry | Update a time entry's description, project, task, tags, billable status, or time range |
clockify_delete_time_entry | Permanently delete a time entry |
clockify_detailed_report | Detailed report: line-by-line time entries for a workspace over a date range, with totals (time, billable time, earned amount) |
clockify_summary_report | Summary report: aggregated time/earnings grouped by one or more dimensions (PROJECT, USER, CLIENT, TASK, TAG, DATE) for a workspace over a d |
FAQ
Does Gemini 1.5 Pro or 2.x support MCP? Yes — Gemini CLI ≥ 0.4 and Vertex AI tools API both accept MCP httpUrl connectors with custom headers.
Next steps
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