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Abhishek-Maheshwari-778

AI Sales Analytics MCP Server

by Abhishek-Maheshwari-778
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Python
Local

⚡ AI Sales Analytics — 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

🤖 Multi-Model AI Fallback Chain

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

1. 🟢 NVIDIA NIM   → Free, 1000 credits (nvapi-...)
2. 🟢 Groq         → Free, no credit card (gsk_...)
3. 🟡 DeepSeek     → Near-free credits (sk-...)
4. 🔵 Rule-Based   → 100% offline, always works

No internet? No API keys? → Rule-based insights still work perfectly!

🚀 Quick Start (5 Minutes)

Step 1 — Install Dependencies

pip install -r requirements.txt

Step 2 — Generate Sample Data (or use your own CSV)

python generate_sample_data.py

Step 3 — Add API Keys (Optional but recommended)

Copy .env.example → .env and fill in your keys:

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

Step 4 — 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

🔑 How to Get FREE API Keys

NVIDIA NIM (Recommended — Best free models)

  1. Go to → https://build.nvidia.com

  2. Click Login / Sign Up (free account)

  3. Go to API Keys → 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 — No credit card)

  1. Go to → https://console.groq.com

  2. Sign up with Gmail or GitHub

  3. Go to API Keys → 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 → https://platform.deepseek.com

  2. Sign up → Go to API Keys → Create

  3. Add to .env: DEEPSEEK_API_KEY=sk-xxxxx

📧 Email Setup (Gmail)

  1. Go to myaccount.google.com

  2. Security → 2-Step Verification (enable)

  3. Security → App passwords → Select "Mail" → 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

📁 Project Structure

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

💬 Agent Chat Examples

python agent.py
You → analyze today's sales
🤖  → Running FULL PIPELINE...
     ✅ Data cleaned (1200 rows)
     ✅ AI insights via NVIDIA NIM
     ✅ Dashboard created
     ✅ PDF exported
     ✅ Email sent

You → show dashboard
🤖  → Opening dashboard in browser...

You → status
🤖  → Total Sales: ₹45,23,400  |  Profit: 18.3%
     Top Product: Laptop Pro X  |  Region: West

You → send report
🤖  → Email delivered to boss@company.com ✓

🔌 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

📊 Dashboard Preview

The HTML dashboard includes:

  • 💰 KPI Cards (Sales, Profit, Orders, Avg Order Value)

  • 📈 Monthly Sales Trend (interactive line chart)

  • 🏅 Top 10 Products (horizontal bar chart)

  • 🗺️ Region-wise Sales (donut chart)

  • 📦 Category Breakdown (bar chart)

  • 🧠 AI-Generated Insights Panel

Opens in Chrome/Edge/Firefox — NO Power BI, NO Microsoft login!

🎓 Resume Description

AI-Powered Sales Analytics Automation using MCP Server

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

📞 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 ❤️ — No Power BI login required. Works 100% locally.

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