What is the Clockify Time Tracker MCP Server?

It's a command-line tool to interact with the Clockify API for managing time entries, listing projects/tags, and generating reports. It is Python-based and leverages the Model Context Protocol (MCP).

What are the prerequisites for using this tool?

You need Python 3.8+ and a Clockify API key.

How do I install the Clockify Time Tracker MCP Server?

Clone the repository and run `pip install -r requirements.txt`.

How do I configure the API key?

Create a .env file with CLOCKIFY_API_KEY=your_clockify_api_key.

Can I integrate this with UBOS?

Yes! Integrating with UBOS allows you to automate time tracking, gain deeper insights, and optimize workflows using AI Agents.

What is MCP and why is it important?

MCP (Model Context Protocol) standardizes how applications provide context to LLMs, enabling AI models to effectively access and utilize data from external sources like Clockify. This improves AI-driven decision-making and automation capabilities.

Is the tool open-source?

Yes, it's open-source, allowing for customization and extension of its functionality.

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Clockify Time Tracker

Name: Clockify Time Tracker
Author: alex198710

Description

Un outil en ligne de commande pour interagir avec l’API Clockify et gérer vos entrées de temps.

Prérequis

Python 3.8+
Clé API Clockify

Installation

Clonez le dépôt
Installez les dépendances :
```
pip install -r requirements.txt
```

Configuration

Créez un fichier .env à la racine du projet avec votre clé API :

CLOCKIFY_API_KEY=votre_clé_api_clockify

Utilisation

Lister les projets

python -m src.cli --workspace WORKSPACE_ID --action list-projects

Lister les tags

python -m src.cli --workspace WORKSPACE_ID --action list-tags

Générer un rapport de temps

python -m src.cli --workspace WORKSPACE_ID --action time-report 
    --project PROJECT_ID 
    --tags TAG1 TAG2 
    --start-date 2024-01-01 
    --end-date 2024-12-31