Polygate MCP Server

A Model Context Protocol server that exposes Polygate business tools to AI clients through a standardized interface.

What It Does

The server allows an MCP-compatible AI client to discover and call business tools such as:

• finding inactive customers

• searching internal knowledge

• drafting customer follow-ups

• creating sales tasks

This demonstrates how an AI assistant can move beyond answering questions and interact directly with business systems.

Related MCP server: Mini-ERP MCP

Why MCP Matters

Businesses often have valuable capabilities spread across internal APIs, databases, CRM systems, documents, and operational software.

Without a common interface, every AI integration requires custom work.

MCP provides a standardized way for AI systems to access business tools and data.

The Polygate MCP Server demonstrates this pattern:

AI Client
↓
Model Context Protocol
↓
Polygate MCP Server
↓
Business Tools / Data / Workflows

Current MCP Tools

get_inactive_customers

Finds customers that have been inactive beyond a specified number of days.

Example use:

Find every customer we haven't contacted in 90 days.

search_polygate_knowledge

Searches Polygate's internal business knowledge.

Example use:

What does Polygate Lead Recovery do?

create_customer_followup

Generates a follow-up draft for an existing customer.

Example use:

Prepare a follow-up for Prime Suites.

create_sales_task

Creates and assigns a business task.

Example use:

Create a task for sales to follow up Prime Suites tomorrow.

Business Applications

This architecture can be expanded into an enterprise MCP layer connecting AI assistants to:

• CRM systems

• customer databases

• ERP platforms

• internal knowledge bases

• hotel management systems

• task management software

• email systems

• messaging systems

• operational databases

• government systems

• internal APIs

Example Enterprise Workflow

A user could ask:

Find every dormant hospitality customer, prepare a reactivation message, and create tasks for the sales team.

An MCP-enabled AI agent could:

1. query customer records

2. identify inactive accounts

3. retrieve relevant customer context

4. draft the outreach

5. create follow-up tasks

6. return the result to the user

This turns natural language into business action.

Tech Stack

• Python

• Model Context Protocol SDK

• MCPServer

• Pytest

• JSON sample data

Project Structure

polygate-mcp-server/
├── app/
│   ├── __init__.py
│   ├── server.py
│   └── tools.py
├── data/
│   ├── customers.json
│   └── knowledge.json
├── tests/
│   └── test_tools.py
├── .gitignore
├── requirements.txt
└── README.md