looker-studio-mcp

looker-studio-mcp

Automates Looker Studio dashboards using Playwright, enabling creation, modification, screenshots, and exports.

Category
Visit Server

README

🎯 Looker Studio MCP (Model Context Protocol)

Automatisation de Looker Studio via Playwright — crĂ©ation, modification, et gestion de dashboards.

Python Playwright License


🚀 FonctionnalitĂ©s

  • ✅ Login Google automatisĂ© avec profil persistant
  • ✅ CrĂ©ation de rapports Looker Studio
  • ✅ Ajout de sources (Google Sheets, BigQuery, etc.)
  • ✅ Ajout de graphiques (Scorecard, Table, Time Series, etc.)
  • ✅ Screenshots de dashboards
  • ✅ Export CSV des donnĂ©es
  • ✅ Listage des rapports existants
  • ✅ Mode interactif avec CLI

📩 Installation

# Cloner le repo
git clone https://github.com/ton-user/looker-studio-mcp.git
cd looker-studio-mcp

# Installer les dépendances
pip install -r requirements.txt

# Installer Chromium pour Playwright
playwright install chromium

🎯 Utilisation

Mode rapide (screenshot)

python3 looker-studio-automation.py screenshot "https://lookerstudio.google.com/report/xxx" /tmp/dashboard.png

Mode interactif

python3 looker-studio-automation.py interactive

Commandes disponibles :

Commande Description
create <titre> Créer un nouveau rapport
list Lister mes rapports
screenshot <path> Capture d'écran
chart <type> Ajouter un graphique
export Exporter en CSV
open <url> Ouvrir une URL
quit Quitter

En tant que module Python

import asyncio
from looker_studio_automation import LookerStudioAutomation

async def main():
    auto = LookerStudioAutomation(headless=False)
    await auto.start()
    
    # Ouvrir Looker Studio
    await auto.open_looker_studio()
    
    # Attendre le login manuel
    input("Connecté? Appuie sur Entree...")
    
    # Créer un rapport
    await auto.create_report("Mon Dashboard")
    
    # Ajouter un graphique
    await auto.add_chart("Scorecard")
    
    # Screenshot
    await auto.take_screenshot("/tmp/dashboard.png")
    
    await auto.stop()

asyncio.run(main())

📁 Structure du projet

looker-studio-mcp/
├── looker-studio-automation.py   # Script principal
├── requirements.txt              # DĂ©pendances Python
├── README.md                     # Documentation
├── LICENSE                       # License MIT
├── .gitignore                    # Fichiers exclus
└── examples/                     # Exemples d'utilisation
    └── example_usage.py

🔧 DĂ©pendances

playwright>=1.40.0

⚠ Pitfalls & Notes

Profil Chrome persistant

Le script utilise un profil Chrome persistant (~/.hermes/looker-studio-chrome/) pour garder la session Google entre les exécutions. Cela évite de se reconnecter à chaque fois.

Login Google

La premiÚre exécution nécessite un login manuel dans le navigateur. Ensuite, la session est sauvegardée.

Sélecteurs CSS

Google modifie rĂ©guliĂšrement les sĂ©lecteurs CSS de Looker Studio. Si le script ne fonctionne plus, il faudra peut-ĂȘtre mettre Ă  jour les sĂ©lecteurs.

Headless mode

Certains éléments UI ne fonctionnent pas en mode headless. Utilisez headless=False pour les opérations complexes.


đŸ€ Contribuer

  1. Fork le projet
  2. Créer une branche (git checkout -b feature/amazing-feature)
  3. Commit (git commit -m 'Add amazing feature')
  4. Push (git push origin feature/amazing-feature)
  5. Ouvrir une Pull Request

📄 License

Ce projet est sous License MIT — voir le fichier LICENSE pour plus de dĂ©tails.


🙏 CrĂ©dits


📧 Contact

Jmarc — jmd@talandria.fr

Projet Link: https://github.com/ton-user/looker-studio-mcp

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured