Model Context Protocol (MCP)

Model Context Protocol (MCP)

Term explanation

Definition and meaning

The Model Context Protocol (MCP) is an open standard developed by Anthropic in 2024 and widely adopted in 2025 by OpenAI, Google, and Microsoft. It defines a standardized way for AI agents to connect to external tools, data sources, and enterprise systems — without requiring custom integrations for every connection. MCP acts as a universal interface: an AI agent with MCP support can securely access databases, APIs, document repositories, and business applications using a consistent protocol, regardless of the underlying system. This dramatically simplifies how AI is embedded into complex enterprise environments.

LIZ AI uses MCP to connect seamlessly to your enterprise systems — CRM, ERP, BI tools, and more. Through standardized MCP integrations, it retrieves live data and feeds it directly into your PowerPoint presentations, automatically and securely.

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Other glossary terms

Massive Open Online Course (MOOC)

Massive open online courses (MOOCs) are large-scale online courses accessible to anyone with an internet connection, often free of charge. MOOCs are delivered through platforms such as Coursera, edX, or Udemy and can attract thousands of learners simultaneously. They typically combine video lectures, readings, quizzes, and discussion forums. MOOCs have democratized access to university-level education and professional skill development worldwide.

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Open Questions

Open questions invite a full, unrestricted response rather than a simple yes or no. They typically begin with words like 'how', 'what', 'why', or 'tell me about'. In presentations, coaching, interviews, and research, open questions encourage deeper thinking, surface underlying perspectives, and generate richer dialogue. They are essential for understanding audience needs, facilitating discussions, and building engagement during interactive sessions.

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AI Grounding

AI grounding is the process of anchoring an AI system's outputs to verified, real-world data rather than relying solely on knowledge encoded during model training. A grounded AI retrieves relevant, up-to-date information from external sources before generating a response. This significantly reduces the risk of AI hallucinations and ensures that outputs are accurate, current, and contextually relevant — a critical requirement for enterprise AI applications where factual reliability is non-negotiable. Grounding is a core technique used in LLM-powered systems.

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Glossophobia

Glossophobia is the fear of public speaking. It is one of the most commonly reported phobias, affecting an estimated 75% of people to some degree. Symptoms range from mild anxiety and nervousness to severe physical reactions such as sweating, shaking, and a racing heart. Glossophobia can significantly limit a person's professional and social opportunities. It is generally treatable through practice, exposure therapy, coaching, and structured presentation skills training.

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