Model Context Protocol (MCP)

The Model Context Protocol (MCP) is an open standard created to make it easier for AI models and applications to access external data, tools, and services in a secure and structured way. Instead of every AI platform building custom integrations, MCP provides a unified protocol that defines how models can connect to external sources—like databases, APIs, file systems, or enterprise apps—through a common interface.

How It Works

1. MCP works as a bridge between an AI model (e.g., GPT) and external systems.
2. It uses servers to expose tools, resources, and data in a standardized format.
3. AI applications can then request context or perform actions via these servers without needing custom connectors each time.

Example:

a. A Robility flow app using MCP could connect to a CRM system to fetch customer data or update records.
b. Instead of building a new integration, it just calls the CRM via MCP.

Key Benefits

1. Interoperability – Works across different LLMs, apps, and services.
2. Extensibility – Developers can easily add new servers for custom data sources.
3. Security – Access to external systems is controlled and sandboxed.
4. Reusability – The same MCP server can be used by multiple AI apps without rewriting integrations.