What is Googledocsmcp

GoogleDocsMCP is a repository designed to create a Model Context Protocol (MCP) that facilitates communication between Google Docs and large language models (LLMs) for extracting valuable insights.

Use cases

Use cases for GoogleDocsMCP include analyzing sales data to identify trends, generating recommendations for marketing strategies, summarizing educational data for performance insights, and facilitating interactive data queries in a collaborative environment.

How to use

To use GoogleDocsMCP, set up the Google Cloud API by enabling the Google Drive and Google Sheets APIs, create a service account, and share the target folder with the service account. Then, obtain an API key from Claude (Anthropic) and set it as an environment variable. After setup, you can load Google Sheets, analyze data, and interact with the MCP using a chat-based interface.

Key features

Key features of GoogleDocsMCP include the ability to load Google Sheets from a specific Drive folder, process them into pandas DataFrames, provide tools like ‘get_insights’ for data analysis and ‘get_future_recommendations’ for actionable suggestions, and a chat-based interface powered by Claude AI.

Where to use

GoogleDocsMCP can be used in various fields such as data analysis, business intelligence, educational settings, and any domain where insights from Google Sheets are valuable.

🧠 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

• [x] Google Cloud project & credentials
• [x] Folder added to My Drive
• [x] Folder shared with service account
• [x] Anthropic key set in env
• [x] 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.