Model Context Protocol (MCP)
Model Context Protocol (MCP) is an open protocol introduced by Anthropic that lets AI agents connect to tools, data sources and applications in a standardised way. It is effectively a common plug-shape between language models and the world they need to read from and act on.
Before MCP, wiring a model to a CRM, a database or an internal API meant writing a bespoke integration per model and per vendor. MCP collapses that into one shape: you publish (or consume) an MCP server, and any compatible AI agent can use it. The model side stays clean, the tool side stays clean, and the glue in the middle stops being one-off code.
In practice, MCP is the connective tissue underneath modern agentic workflows. Where function calling defines how a single large language model invokes a tool inside its own runtime, MCP defines how tools, resources and prompts are exposed across the wider system — across models, vendors and clients.
The honest take: MCP is emerging fast and worth understanding now, not later. It changes how teams wire tools to models, and the projects that adopt it early end up with a much smaller integration surface to maintain. The rule of thumb is to expose your internal capabilities as MCP servers once, rather than rebuild that bridge for every new model or agent framework that comes along.
