AI & Automation
What is Model Context Protocol (MCP)?
Definition
An open standard that defines how AI models connect to external tools, data sources, and services — the 'USB-C port' for AI integrations, developed by Anthropic.
In more detail
MCP (Model Context Protocol) standardises the interface between AI models and external resources — databases, APIs, file systems, cloud services, and custom internal tools. Before MCP, every integration required bespoke glue code. MCP defines a consistent protocol that any model and any tool can implement once and then connect to everything else.
The architecture is client-server: a host application (like Claude Desktop or a custom AI app) connects to MCP servers via a standard protocol. Each MCP server exposes tools and data in a consistent format — read a database, search files, call an API — and the AI model can invoke any of them without custom integration code per tool.
MCP servers exist for PostgreSQL, SQLite, Google Drive, GitHub, Slack, Brave Search, and dozens of other services. Building on MCP means your AI system can connect to new tools by adding a server, not rewriting your agent.
Why it matters
MCP is rapidly becoming the standard for enterprise AI integrations. Companies evaluating AI solutions should ask whether the system supports MCP — it significantly reduces future integration effort and vendor lock-in.
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