Claude’s Model Context Protocol: A New Era for LM Applications

Introducing the Model Context Protocol

The Model Context Protocol (MCP) is an open protocol that revolutionizes the integration of large language models (LLMs) with diverse web data sources and tools.

MCP establishes a standardized approach to connecting LLMs with the context they need to perform their tasks. Think of it as a bridge that enables LLMs to access essential data, including web search results, Slack messages, GitHub source code, and Google Docs.

The Rise of AI Agents

Organizations have been exploring innovative ways to empower AI with data and instructions. AI agents have emerged as a key solution, allowing users to control AI through various methods.

OpenAI’s Operator, Claude’s Copilot, Microsoft’s Maventic-1, and Codex from GitHub Copilot are examples of AI agents that provide different approaches to granting LLMs access to data and orchestrating their actions.

Claude’s MCP: A Balanced Approach

While Claude’s MCP may not have garnered the same level of attention as OpenAI’s announcement, it represents a significant advancement.

The unique aspect of Claude’s MCP lies in its API-based approach to context connectivity. This provides several advantages:

• Improved security and control: Unlike granting AI full control over a computer or browser, API-based access limits potential security risks and allows for granular control.
• Data usage control: By accessing data via APIs, LLMs are subject to the access permissions and controls of the underlying data sources.

Claude’s MCP thus strikes a balance between maximizing the data available to LLMs while minimizing the risk of unintended consequences.