analyze-dataLABSCO SUMMARY
It can send mail, so treat the credential accordingly.
Most analysis servers stop at producing output; this one delivers it, which means you are handing an assistant a working sending credential on your address. Use a dedicated account and an app password, and be deliberate about what goes into a draft — the project's own notes make the same point. The analysis half stands on its own if you would rather not wire up email at all.
What it is
Three steps of a reporting workflow in one server: statistical analysis of a data file, generation of written research content, and delivery by email — with the subject line itself written by the model.
What you get
analyze-datatakes an Excel or CSV file, detects and parses types, runs statistics over numeric columns including correlation and outlier detection, and writes an HTML report with interactive Chart.js plots — with a basic and a detailed mode and a configurable output directorygenerate-thinkingproduces research papers, technical documentation, data-analysis summaries and business-intelligence reports from a prompt, saving each response with a timestampsend-emaildelivers the result over SMTP with plain text and HTML bodies, image attachments that can display inline, and a subject line generated from a prompt rather than typed- Output lands in a predictable structure — analysis reports and plots, generated content and email logs each in their own folder
Requirements
Node.js v16 or higher and TypeScript. Clone, install and build, then point the client at the compiled entry point. Three credentials are needed: GEMINI_API_KEY for the model, and NODEMAILER_EMAIL with NODEMAILER_PASSWORD for sending — for Gmail that has to be an app password rather than the account password. Supported input formats are .xlsx, .xls and .csv, in UTF-8.
Setup effort
Build from source — git clone https://github.com/falahgs/Gemini-Data-Analysis-Research-MCP-Server.git
USE CASES
01
Getting a first read on a spreadsheet
Point at the file and get statistics, correlations and outliers back as a report you can open.
02
Turning findings into something readable
Generate the write-up from the analysis rather than composing it from the numbers by hand.
03
Sending the result to whoever asked for it
Deliver the report with its charts inline, and let the subject line be written for you.
3 tools
Listed in project docs. Your client may show a different list.
send-emailgenerate-thinkingBEFORE YOU INSTALL
What to know first
Tools you get
3 tools named in the project's documentation.
Requires
- node on PATH
- Node.js
- GEMINI_API_KEY in your environment
- NODEMAILER_PASSWORD in your environment
- NODEMAILER_EMAIL in your environment
Where it runs
The documented client runs the server on your machine.
INSTALLATION
Connect your client
You clone and build this one yourself.
Server setup
TERMINAL
git clone https://github.com/falahgs/Gemini-Data-Analysis-Research-MCP-Server.git
cd Gemini-Data-Analysis-Research-MCP-Server
npm installCreate a .env file in the clone with GEMINI_API_KEY, NODEMAILER_EMAIL and NODEMAILER_PASSWORD
TERMINAL
npm run buildMCP Clients
Claude Desktop
CLAUDE DESKTOP · JSON
{
"mcpServers": {
"Gemini Data Analysis": {
"command": "node",
"args": [
"<YOUR_PATH_TO_GEMINI_DATA_ANALYSIS_EMAIL>/dist/index.js"
],
"cwd": "<YOUR_PATH_TO_GEMINI_DATA_ANALYSIS_EMAIL>",
"env": {
"GEMINI_API_KEY": "<YOUR_GEMINI_API_KEY>",
"NODEMAILER_EMAIL": "<YOUR_NODEMAILER_EMAIL>",
"NODEMAILER_PASSWORD": "<YOUR_NODEMAILER_PASSWORD>"
}
}
}
}<YOUR_PATH_TO_GEMINI_DATA_ANALYSIS_EMAIL> is the full path to your clone, in args as well as cwd (the folder git clone creates is named Gemini-Data-Analysis-Research-MCP-Server). <YOUR_NODEMAILER_EMAIL> and <YOUR_NODEMAILER_PASSWORD> are the address you send from and its app password (for Gmail, an app password, not the account password).
