🧠 Google Sheets Analyzer MCP (Model Context Protocol)

This project is an implementation of a Model Context Protocol (MCP)-based system that allows you to:

• Read and analyze Google Sheets from a specific Google Drive folder
• Use tools like get_insights, get_future_recommendations, etc.
• Ask questions and get responses using Claude AI (Anthropic)

📂 Project Structure

├── flows/
├── lib/
│   └── server/
│       └── server.py         # Loads sheets from Google Drive and exposes MCP tools
│   └── client/
│       └── client.py         # Connects to MCP server and queries using Claude
├   └── configs/
│        └── configuration.py # Centralized config file
├── environment.yml           # Conda environment definition
├── README.md

⚙️ Features

• ✅ Load Google Sheets from a specific Drive folder
• ✅ Process and convert them into pandas DataFrames
• ✅ Tools:
  • get_insights: Analyze the data and summarize trends
  • get_future_recommendations: Suggest actions based on insights
• ✅ Chat-based interface powered by Claude AI
• ✅ Fully functional MCP Server/Client architecture

🏗️ Setup Guide

1. 🔐 Google Cloud API Setup

✅ Enable APIs

• Go to Google Cloud Console
• Enable:
  • Google Drive API
  • Google Sheets API

✅ Create a Service Account

• Go to APIs & Services > Credentials > Create Credentials > Service Account
• Assign roles like Viewer or Drive Reader
• Click on your service account → "Keys" → Add new key → JSON
• Save the file as credentials/gcp_credentials.json

✅ Share Folder with Service Account

• Copy the client_email from the gcp_credentials.json
• Go to Google Drive → open the target folder → Share with the client email

2. 🤖 Get Claude (Anthropic) API Key

1. Go to https://console.anthropic.com
2. Get your API key under “API Keys”
3. Set it as an environment variable:

export ANTHROPIC_API_KEY="your-api-key"

📦 Create & Activate Conda Environment

conda env create -f environment.yml
conda activate gsheet-mcp

You can override these using .env or export in your terminal.

🚀 How to Run

1. Start the MCP Server

python lib/server/server.py

It will:

• Authenticate using your Google credentials
• Load spreadsheets from the target folder
• Start a FastMCP server exposing tools like get_insights

2. Run the MCP Client

In a new terminal (same environment):

python lib/client/client.py

You can then start chatting with Claude and ask things like:

What are the top insights from the inventory sheet?
What future recommendations can you give for budgeting?
Summarize fund trends across all files.

🧪 Example Prompt

"Give me future recommendations based on trends from all spreadsheets. Be concise and format your answer in bullet points."

✅ Checklist

• Google Cloud project & credentials
• Folder added to My Drive
• Folder shared with service account
• Anthropic key set in env
• Claude model set to claude-3-haiku-20240307

🛠️ TODO / Ideas

• Add authentication via gcloud auth (for personal scripts)
• Support other Claude models via config
• Add tool for plotting charts from sheet data
• Use embeddings to auto-suggest questions

🧑‍💻 Credits

Created by [Harri200191!] to explore Claude-powered spreadsheet analytics with MCP.