The agentic web envisions a future where AI agents perform tasks for users, prompting a need for websites to be designed for AI understanding. Publishers must adapt their content for accessibility in AI tools to remain relevant. Model Context Protocol (MCP), developed by Anthropic, serves as a framework to connect AI applications with external data sources. It functions similarly to robots.txt but for AI, allowing publishers to control how their content is shared. MCP facilitates easier communication between large language models and applications, supporting the transition for publishers into this new AI-driven landscape.
Model Context Protocol, or MCP, standardizes how an AI application connects to external sources. It was developed by AI company Anthropic and released in open-source last November.
MCP is kind of like robots.txt for AI, in which publishers can structure how content is shared with AI systems.
Data can go into an MCP server, making it easier for LLMs to understand.
If publishers want to have their content surfaced in AI tools, they need to figure out how to make their content accessible to AI agents.
Collection
[
|
...
]