AI BriefingMCP Emerges as the Standard for Connecting LLMs to External Systems… Solving the MxN Problem and Enabling Dynamic Tool Discovery
Key point
MCP standardizes connections between LLMs and external systems, solving the MxN problem and enabling dynamic tool discovery.
Details
Core Value and Working Principles of MCP
Model Context Protocol (MCP) is an open standard that enables LLMs to connect to external data sources and systems, providing a consistent pathway for AI agents to access real-time data and execute external tools. Unlike traditional tool/function calling, which required custom connections between LLMs and external systems, MCP solves the MxN problem (inefficient connections between M agents and N tools) through a standardized bidirectional communication model, reducing the number of connections to M+N.
MCP operates through a four-step workflow: discover, decide, call, review. Upon starting an AI agent, it queries the connected MCP server for a catalog of data sources and functions, passing this information to the LLM context window. The LLM then determines whether external resources are needed to process the request and contacts the system via the corresponding MCP connection. During this process, runtime discovery allows for the automatic recognition of new tools or database field changes without code modifications.
Architecture and Real-World Application Cases
The MCP architecture consists of an MCP Client that communicates with external systems and an MCP Server that attaches to external systems such as calendars, email, and CRM to expose resources and tools. This standard, released by Anthropic in November 2024, was donated to the Agentic AI Foundation in 2025 and is being rapidly adopted by major LLM developers.
ElevenLabs is a representative case of performing bidirectional roles as both an MCP server and client. The ElevenLabs-hosted MCP server provides OAuth-based secure connections to AI assistants like Claude, enabling agent creation and cost comparison via natural language prompts. Additionally, the ElevenLabs workspace connects to external servers such as Zapier MCP to access hundreds of services like Salesforce, supporting complex agent workflows that query backend systems in real-time to generate voice responses during customer inquiries.
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