Where MCP Fits in AI Apps
MCP is not the AI model. MCP is not the database. MCP is the connection layer that helps AI applications communicate with external systems in a standard way.
The user talks to the AI app. The AI app uses the LLM to understand and respond. When outside information is needed, MCP helps connect to external systems. Click each block below to explore its role.
A connection standard
A way to access external systems
A bridge between AI apps and outside data
Useful when many domains are involved
The AI model
A vector database
A replacement for RAG
A replacement for APIs
A guarantee that answers are correct
Direct knowledge search
Bring outside information
The AI app can search a vector database directly. MCP is a separate optional path when the app needs information from an external system.
MCP does not remove APIs. It gives the AI app a standard way to work with systems that may still use APIs internally.
Function Calling can decide what action is needed. MCP can provide the path to perform it.
Choose what your AI app needs. The builder shows which pieces usually appear.
MCP is a connection layer for AI applications.
MCP helps AI apps communicate with external systems.
MCP can work with LLMs, RAG, APIs, tools, and databases.
MCP does not replace the LLM or RAG.
MCP is most useful when an AI app needs access to multiple external systems.
MCP fits between AI applications and external domains. It gives AI apps a standard way to connect to business domains and data sources while the LLM still handles understanding and response generation.