What is MCP?

MCP (Model Context Protocol) is an open standard that allows AI assistants to securely connect with external data sources and tools.

The Basics

Think of MCP as a universal adapter:

AI applications (like Billix) speak MCP
External servers provide tools via MCP
They connect and communicate seamlessly

How It Works

[Billix] <--MCP Protocol--> [MCP Server] <--> [Your Data/Tools]

Billix sends a request to the MCP server
MCP Server processes the request
Server returns data or executes tools
Billix uses the response in your conversation

What MCP Servers Provide

Tools

Functions the AI can call:

Database queries
API calls
Calculations
File operations

Resources

Data the AI can access:

Documents
Database records
Real-time information
Configuration data

Prompts

Pre-defined prompt templates:

Standard workflows
Domain-specific instructions
Best practices

Benefits of MCP

Standardization

One protocol works everywhere:

Connect any MCP server
No custom integration needed
Community compatibility

Security

Controlled access:

Authentication required
Permissions defined
Audit logging

Flexibility

Use what you need:

Self-host servers
Use community servers
Build custom servers

MCP vs Other Approaches

Approach	Pros	Cons
MCP Servers	Standardized, powerful	Requires server setup
Custom Tools	Simple, hosted by Billix	Limited to API/code
Integrations	Pre-built, easy	Only supported services

When to Use MCP

Use MCP when:

You have complex internal systems
You want to use community-built servers
You need real-time data access
You're building for multiple AI platforms

Use Custom Tools when:

You have simple API needs
You don't want to host a server
Quick setup is priority

Security Considerations

Authentication

MCP supports multiple auth methods:

API keys
Bearer tokens
Basic auth
Custom headers

Data Privacy

Data stays between Billix and the server
Server owner controls access
No data stored by protocol