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Model Context Protocol (MCP)

The Model Context Protocol (MCP) is an open standard developed by Anthropic that provides a universal way to connect AI models to external data sources, tools, and services. MCP standardizes how AI applications communicate with integrations — similar to how USB standardized peripheral connections. It enables AI agents to access databases, APIs, file systems, and other services through a consistent interface.

Example

A developer configures MCP servers for their AI coding assistant — one connects to their GitHub repository, another to their database, and a third to their project management tool. The AI can now read code, query data, and update tickets through a single standardized protocol, without custom integration code for each service.

Frequently asked questions

What is Model Context Protocol (MCP)?

The Model Context Protocol (MCP) is an open standard developed by Anthropic that provides a universal way to connect AI models to external data sources, tools, and services. MCP standardizes how AI applications communicate with integrations — similar to how USB standardized peripheral connections.

Can you give an example of Model Context Protocol (MCP)?

A developer configures MCP servers for their AI coding assistant — one connects to their GitHub repository, another to their database, and a third to their project management tool. The AI can now read code, query data, and update tickets through a single standardized protocol, without custom integration code for each service.

Related Terms

Agentic AITool Use (Function Calling)Large Language Model (LLM)Retrieval-Augmented Generation (RAG)

Related Resources

Blog Post

Model Context Protocol (MCP): The Complete 2026 Guide

MCP is the open standard from Anthropic that lets any compliant LLM client talk to any compliant tool, resource, or prompt server — collapsing the n×m integration problem into n+m.

Blog Post

MCP and Tool Use Prompting: How to Write Prompts for AI That Uses Tools (2026)

AI models don't just generate text anymore — they call APIs, query databases, and execute code. Learn how to write prompts that guide tool-using AI effectively, from function calling basics to MCP server architecture.