Definition

MCP (Model Context Protocol) is an open-source protocol that enables AI applications to securely connect with external data sources and tools. It provides a standardized way for AI models to access and interact with various systems, databases, and services while maintaining security and data integrity. MCP acts as a bridge between AI applications and the broader software ecosystem, allowing for more dynamic and contextually-aware AI interactions.

What problem does MCP solve for AI applications?

MCP addresses the challenge of AI models being isolated from real-time data and external systems. Without MCP, AI applications often work with static or limited information. MCP allows AI models to access live databases, APIs, file systems, and other tools, making them more useful and accurate for real-world business applications.

How does MCP ensure security when connecting AI to external systems?

MCP includes built-in security features such as authentication mechanisms, permission controls, and secure communication channels. It allows organizations to define exactly what data and tools an AI application can access, ensuring that sensitive information remains protected while still enabling useful AI functionality.

Do I need to be a developer to use MCP?

While MCP is a technical protocol, many low-code platforms and AI tools are incorporating MCP support with user-friendly interfaces. This means business users can often benefit from MCP-enabled features without needing to understand the underlying technical implementation.

What types of external systems can MCP connect to?

MCP can connect to a wide variety of systems including databases (SQL, NoSQL), file storage systems, web APIs, business applications (CRM, ERP), cloud services, and custom tools. The protocol is designed to be flexible and extensible to support virtually any type of data source or service.

How does MCP differ from traditional API integrations?

Unlike traditional APIs that require custom integration work for each connection, MCP provides a standardized protocol that AI applications can use to connect to multiple systems consistently. This reduces development time and complexity while providing better security and context management specifically designed for AI use cases.