AI Sales Analytics MCP Server

AI Sales Analytics MCP Server

Automates sales data analysis by cleaning CSV, generating AI insights, creating interactive HTML dashboards, exporting PDF reports, and emailing them, all via MCP tools and multi-model AI fallback.

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README

⚑ AI Sales Analytics β€” MCP Automation System

No Power BI Login. No Manual Work. Just drop a CSV and AI does everything.


🎯 What This Does

You Do System Does Automatically
Drop a .csv file Detects it instantly
Nothing Cleans & validates data
Nothing AI generates business insights
Nothing Creates interactive HTML dashboard
Nothing Exports professional PDF report
Nothing Emails report to anyone

πŸ€– Multi-Model AI Fallback Chain

The system automatically tries each AI provider and falls back if unavailable:

1. 🟒 NVIDIA NIM   β†’ Free, 1000 credits (nvapi-...)
2. 🟒 Groq         β†’ Free, no credit card (gsk_...)
3. 🟑 DeepSeek     β†’ Near-free credits (sk-...)
4. πŸ”΅ Rule-Based   β†’ 100% offline, always works

No internet? No API keys? β†’ Rule-based insights still work perfectly!


πŸš€ Quick Start (5 Minutes)

Step 1 β€” Install Dependencies

pip install -r requirements.txt

Step 2 β€” Generate Sample Data (or use your own CSV)

python generate_sample_data.py

Step 3 β€” Add API Keys (Optional but recommended)

Copy .env.example β†’ .env and fill in your keys:

copy .env.example .env
# Edit .env with your keys

Step 4 β€” Run the Pipeline!

# Option A: Run once on existing data
python main.py

# Option B: Watch folder (auto-trigger on CSV drop)
python watcher.py

# Option C: Chat with AI agent
python agent.py

πŸ”‘ How to Get FREE API Keys

NVIDIA NIM (Recommended β€” Best free models)

  1. Go to β†’ https://build.nvidia.com
  2. Click Login / Sign Up (free account)
  3. Go to API Keys β†’ Create API Key
  4. Copy key (starts with nvapi-)
  5. Add to .env: NVIDIA_API_KEY=nvapi-xxxxx

Free tier: 1000 inference credits. Model: meta/llama-3.3-70b-instruct

Groq (Fastest β€” No credit card)

  1. Go to β†’ https://console.groq.com
  2. Sign up with Gmail or GitHub
  3. Go to API Keys β†’ Create API Key
  4. Copy key (starts with gsk_)
  5. Add to .env: GROQ_API_KEY=gsk_xxxxx

Free tier: Generous rate limits, no card needed. Model: llama-3.3-70b-versatile

DeepSeek (Very cheap)

  1. Go to β†’ https://platform.deepseek.com
  2. Sign up β†’ Go to API Keys β†’ Create
  3. Add to .env: DEEPSEEK_API_KEY=sk-xxxxx

πŸ“§ Email Setup (Gmail)

  1. Go to myaccount.google.com
  2. Security β†’ 2-Step Verification (enable)
  3. Security β†’ App passwords β†’ Select "Mail" β†’ Generate
  4. Copy 16-char password (e.g. abcd efgh ijkl mnop)
  5. Add to .env:
    EMAIL_SENDER=you@gmail.com
    EMAIL_PASSWORD=abcdefghijklmnop
    EMAIL_RECEIVER=boss@company.com
    

πŸ“ Project Structure

AI-PowerBI-MCP-Automation/
β”‚
β”œβ”€β”€ πŸ“‚ data/
β”‚   β”œβ”€β”€ sales.csv              ← Your input CSV
β”‚   └── cleaned_sales.csv      ← Auto-generated
β”‚
β”œβ”€β”€ πŸ“‚ reports/                ← All outputs here
β”‚   β”œβ”€β”€ dashboard.html         ← 🌐 Open in browser!
β”‚   β”œβ”€β”€ report.pdf             ← πŸ“„ Professional report
β”‚   └── insights.json          ← Raw KPI data
β”‚
β”œβ”€β”€ πŸ“‚ incoming/               ← DROP CSV HERE for auto-trigger
β”‚
β”œβ”€β”€ πŸ“‚ src/
β”‚   β”œβ”€β”€ ai_engine.py           ← Multi-model AI fallback
β”‚   β”œβ”€β”€ clean_data.py          ← Data cleaning
β”‚   β”œβ”€β”€ insights.py            ← KPI + AI insights
β”‚   β”œβ”€β”€ dashboard.py           ← HTML dashboard (replaces Power BI)
β”‚   β”œβ”€β”€ export_pdf.py          ← PDF report
β”‚   └── send_email.py          ← Email automation
β”‚
β”œβ”€β”€ πŸ“‚ mcp_server/
β”‚   └── server.py              ← MCP server (AI agent tools)
β”‚
β”œβ”€β”€ main.py                    ← Run full pipeline
β”œβ”€β”€ watcher.py                 ← Folder auto-watcher
β”œβ”€β”€ agent.py                   ← Chat interface
β”œβ”€β”€ generate_sample_data.py    ← Generate test data
β”œβ”€β”€ config.py                  ← All settings & API keys
β”œβ”€β”€ .env.example               ← Key template
└── requirements.txt

πŸ’¬ Agent Chat Examples

python agent.py
You β†’ analyze today's sales
πŸ€–  β†’ Running FULL PIPELINE...
     βœ… Data cleaned (1200 rows)
     βœ… AI insights via NVIDIA NIM
     βœ… Dashboard created
     βœ… PDF exported
     βœ… Email sent

You β†’ show dashboard
πŸ€–  β†’ Opening dashboard in browser...

You β†’ status
πŸ€–  β†’ Total Sales: β‚Ή45,23,400  |  Profit: 18.3%
     Top Product: Laptop Pro X  |  Region: West

You β†’ send report
πŸ€–  β†’ Email delivered to boss@company.com βœ“

πŸ”Œ MCP Server (For AI Agents like Claude)

Add to your Claude Desktop mcp_settings.json:

{
  "mcpServers": {
    "ai-sales-analytics": {
      "command": "python",
      "args": ["C:/path/to/mcp_server/server.py"]
    }
  }
}

Available MCP Tools:

Tool Description
run_full_pipeline Run everything end-to-end
clean_data Clean CSV file
generate_insights Get AI insights + KPIs
create_dashboard Build HTML dashboard
export_pdf Generate PDF report
send_email Email the report
get_status Check system status

πŸ“Š Dashboard Preview

The HTML dashboard includes:

  • πŸ’° KPI Cards (Sales, Profit, Orders, Avg Order Value)
  • πŸ“ˆ Monthly Sales Trend (interactive line chart)
  • πŸ… Top 10 Products (horizontal bar chart)
  • πŸ—ΊοΈ Region-wise Sales (donut chart)
  • πŸ“¦ Category Breakdown (bar chart)
  • 🧠 AI-Generated Insights Panel

Opens in Chrome/Edge/Firefox β€” NO Power BI, NO Microsoft login!


πŸŽ“ Resume Description

AI-Powered Sales Analytics Automation using MCP Server

β€’ Built an end-to-end agentic AI pipeline using Python, MCP Server, and multi-model AI
β€’ Implemented intelligent fallback: NVIDIA NIM β†’ Groq β†’ DeepSeek β†’ Rule-based insights
β€’ Automated CSV ingestion, data cleaning, KPI generation, and interactive dashboard creation
β€’ Replaced Power BI with custom Plotly HTML dashboards (no login required)
β€’ Integrated watchdog folder monitoring for zero-touch automation
β€’ Delivered PDF reports and email notifications via SMTP automation
β€’ Exposed pipeline as MCP tools enabling AI agents to analyze data through natural language

πŸ“ž Tech Stack

Layer Technology
Data Python + Pandas
AI NVIDIA NIM / Groq / DeepSeek / Rule-based
Dashboard Plotly (interactive HTML)
PDF ReportLab
Email SMTP (Gmail)
Automation Watchdog
AI Protocol MCP (Model Context Protocol)

Built with ❀️ β€” No Power BI login required. Works 100% locally.


🌐 Web Interface (Addon)

A new interactive web interface is available!

  1. Run python app.py
  2. Open http://localhost:8000
  3. Enjoy Drag & Drop uploads, Multi-Domain support (Sales, Health, Trading), and automatic saving of API keys.

🟑 Power BI Integration (.pbids)

The pipeline now automatically generates an optimized .pbids file. Double-clicking this file opens Power BI instantly connected to your clean data, allowing you to bypass Power Query entirely.


πŸ‘¨β€πŸ’» About the Developers

  • Abhishek Maheshwari (Developer): Engineered this pipeline to showcase advanced AI agentic workflows, multi-model LLMs, and Python data engineering.
  • Harshit Varshney (Mentor): Google, IBM, and HubSpot Certified. LinkedIn Profile

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