lavanya-enterprise-mcp-server

lavanya1402/lavanya-enterprise-mcp-server

3.2

If you are the rightful owner of lavanya-enterprise-mcp-server and would like to certify it and/or have it hosted online, please leave a comment on the right or send an email to dayong@mcphub.com.

Corp Secure Supervisor is an enterprise-grade AI automation system designed to streamline secure internal workflows using Agentic AI.

Tools
1
Resources
0
Prompts
0

Corp Secure Supervisor — Azure Agents × MCP × RBAC × PII

Architected by Lavanya Srivastava (Enterprise Agentic AI Architect)

🌟 Overview

Corp Secure Supervisor is an enterprise-grade AI automation system that demonstrates how modern companies use Agentic AI to automate secure internal workflows.

A manager gives one natural-language request, and the system:

  • Checks calendar availability
  • Schedules meetings
  • Drafts formal internal emails
  • Applies RBAC (Role-Based Access Control)
  • Sanitizes PII before communication
  • Sends the final output safely

This prototype mirrors production systems used inside Microsoft, Deloitte, Accenture, Wells Fargo, Walmart Tech, TCS, Infosys, and other global enterprises.

🧠 What Makes This Project Different

Most demos show simple Q&A chatbots. This is a full enterprise workflow orchestration system.

It combines:

✔ Azure Supervisor Agents

Understands the manager’s request and decides which secure tools to call.

✔ MCP (Model Context Protocol) Custom Tooling

Your own tools for availability check, scheduling, email drafting, and secure communication.

✔ RBAC Enforcement

Agent checks who is allowed to do what.

✔ PII Sanitization

Sensitive information is removed before any email is sent.

✔ Streamlit Business UI

A clean interface that simulates how business managers interact with internal AI systems.

✔ Hybrid Cloud via ngrok

Your MCP tools run locally but securely connect to Azure through HTTPS.

🏗 Architecture (High-Level)

No code. Only conceptual clarity.

Manager Request →
  Azure Supervisor Agent →
    MCP Secure Tools →
      RBAC + PII Guardrails →
        Safe Automated Output →
          Streamlit UI

This architecture reflects real enterprise AI production systems.

🏢 Real Corporate Use Cases

This system can automate:

  • Emergency escalation workflows
  • Incident management & scheduling
  • HR communications
  • Compliance-safe email generation
  • Customer issue triaging
  • Shift planning & internal coordination

📁 Project Structure

lavanya-enterprise-mcp-server/
│
├── mcp_server/
│   └── corp_mcp_server.py             # Custom MCP tools (FastMCP)
│
├── azure_agent_client/
│   └── connect_mcp_agent.py           # Connect MCP to Azure Supervisor Agent
│
├── streamlit_azure_mcp_app.py         # Streamlit front-end (Manager UI)
│
├── .env                               # Local secrets (ignored by Git)
├── requirements.txt
├── .gitignore
└── LICENSE

🌍 ngrok Integration

MCP server runs locally and is securely exposed to Azure through ngrok, showcasing:

  • Hybrid on-prem + cloud integration
  • Real networked tool calling
  • Production-style architecture

Recruiters immediately understand this as practical enterprise engineering.

🎯 Skills Demonstrated

This project showcases:

  • Agentic AI Systems
  • Azure AI Foundry
  • MCP Tooling
  • Enterprise RBAC + PII Guardrails
  • Workflow Automation
  • Streamlit Engineering
  • Cloud + Local Hybrid AI
  • Secure System Design

🏆 More About This Project

  • Build real enterprise systems, not demos
  • Automate complex workflows end-to-end
  • Architect secure, scalable, multi-agent systems
  • enterprise AI solutions architecture
  • production-style prototypes

📜 Footer

Designed & Orchestrated by Lavanya Srivastava Enterprise Agentic AI Architect (Azure + MCP + Cloud Automations)

image