What is Model Context Protocol (MCP)?
Model Context Protocol (MCP) is an open standard, introduced by Anthropic in November 2024, that lets AI applications connect to tools and data sources through one common protocol instead of custom integrations.
How It Works
MCP gives AI applications one standard way to reach tools and data. Servers expose tools, resources and prompts, and clients connect to them. Clients include Claude, ChatGPT, Gemini, Copilot, Cursor and VS Code. Anthropic introduced MCP in November 2024, and on December 9, 2025 it donated the protocol to the Agentic AI Foundation, a directed fund under the Linux Foundation. For example, one MCP server for a company's CRM can be used by several different AI apps, so it is built once rather than once per app. Platforms such as n8n can act as both an MCP client and an MCP server.
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Key Benefits
- One protocol instead of a custom integration per AI app
- Servers expose tools, resources and prompts in a consistent way
- Works across clients such as Claude, ChatGPT, Gemini, Copilot, Cursor and VS Code
- Open standard under the Linux Foundation's Agentic AI Foundation
- Lets agents reach live business data and actions
Common Use Cases
- Letting an AI agent search a company knowledge base
- Connecting an assistant to a CRM or ticketing system
- Giving a coding assistant access to project tools and docs
- Exposing automation workflows as tools to an AI app
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Related Terms
Workflow Automation
The use of technology to automate repeatable business processes, reducing manual intervention and ensuring tasks are completed consistently and efficiently.
AI Agents
Autonomous software programs powered by artificial intelligence that can perceive their environment, make decisions, and take actions to accomplish specific goals.
n8n
n8n is a node-based workflow automation platform, source-available under a fair-code license, that connects apps and services through visual workflows and includes an AI Agent node for building LLM-driven automations.
Large Language Model (LLM)
A large language model (LLM) is a neural network trained on very large text collections to predict the next token, which lets it understand and generate human language for tasks like answering, summarizing and drafting.
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