Model Context Protocol (MCP)
The open standard connecting AI to external tools — Universal Translator Protocol for models that need to speak to other systems.
Model Context Protocol (MCP), released by Anthropic in late 2024, defines a standard client-server interface that allows any AI model to communicate with any MCP-compatible tool server using a common message format and protocol. Before MCP, integrating an LLM with external tools required custom code for each integration — a different API client, authentication mechanism, and data format for every tool. MCP standardizes this: tool servers implement the MCP server interface, AI clients implement the MCP client interface, and any combination of compatible clients and servers can connect. The result is an ecosystem where developers build MCP servers once (for databases, APIs, file systems, web services) and any MCP-compatible AI model can use them without additional integration work.
MCP has gained rapid adoption among AI development tools, with servers available for GitHub, Slack, Google Drive, databases, web browsing, code execution, and dozens of other services. The protocol defines three types of capabilities that servers can expose: Resources (data that can be read, like files or database records), Tools (functions that can be called, like writing a file or sending a message), and Prompts (reusable interaction templates). Servers can expose any combination of these capabilities, and AI clients can discover and use what's available. This makes MCP a foundational piece of the AI tooling ecosystem — similar to how USB standardized peripheral device connections, MCP standardizes AI-to-tool connections.
For B2B development and IT teams building AI-powered applications, MCP significantly reduces the engineering cost of connecting AI models to existing systems. Rather than writing custom API integration code for every tool an AI agent needs to use, teams can install or build MCP-compatible servers for their key systems and connect them with minimal configuration. For content and marketing teams, MCP servers exist for CMSes, analytics platforms, social media tools, and asset management systems — enabling AI workflows that can automatically pull performance data, access content libraries, and publish to distribution channels without custom engineering for each integration.
Related terms
- Tool Use— Mr. Spock accessing the ship's computer mid-answer — the AI calling external systems without being asked to.
- Function Calling— The AI pulling a lever that triggers a real-world action — pushing a button on the Enterprise bridge that actually does something.
- AI Agent— Software that acts without being told what to do next — like house elves, except they work for everyone and can quit.
- AI Orchestration— Picard managing the bridge crew across systems — everyone with a role, everything in sequence, one mission.