Model Context Protocol (MCP)
An open protocol authored by Anthropic that standardizes how LLM applications discover, invoke, and stream from external tools, resources, and prompt templates. MCP treats tool discovery as a first-class runtime concern rather than requiring per-integration glue code.
Related terms
- Tool Use
The capability of AI models to invoke external tools, APIs, and systems to accomplish tasks. Modern implementations rely on structured outputs (JSON schemas or function signatures) so the model's tool calls can be parsed and executed reliably. Extends AI beyond text generation into real-world actions.
- AI Agent
An autonomous AI system that can perceive its environment, make decisions, and take actions to achieve specific goals. Agents can use tools, interact with APIs, and coordinate with other agents.
- A2A Protocol
Agent-to-Agent protocol — an emerging standard for enabling autonomous agents (potentially built on different frameworks or hosted by different vendors) to advertise capabilities, negotiate tasks, and collaborate over a common wire format.
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Next steps
- Take the assessment— See where you stand
Call this framework and its tools from your own agent via the Model Context Protocol (MCP) server. Works with Claude Desktop, Cursor, Zed, Continue, and the OpenAI Agents SDK.
Where this fits
Model Context Protocol (MCP) is part of the Agentic AI vocabulary used in the Generative AI Maturity Framework. See the full glossary for the complete set of 149 defined terms, or take the free maturity assessment to see where your organisation stands.