MCP (Model Context Protocol) is an open-source standard protocol developed by Anthropic, designed to solve the challenge of connecting large language models with external data sources and tools. It builds upon existing function calling mechanisms, eliminating the need for custom integration between LLMs and various applications.
Core Concepts:
- MCP is a standardized communication protocol that defines how LLMs interact with external tools, data sources, and services
- It acts as a "universal remote control" between AI models and external systems
- Developers don't need to redesign interfaces for every combination of AI model and external system
Key Features:
- Standardized Interface: Provides unified protocol specifications that different tools can follow
- Simplified Integration: Reduces custom development work and improves development efficiency
- Context Awareness: Enables LLMs to better understand and utilize external resources
- Extensibility: Supports connections to multiple data source and tool types
Use Cases:
- Database queries and operations
- API calls and service integration
- File system access
- Real-time data retrieval
- Third-party service integration
Technical Architecture: MCP defines standards for message formats, tool registration, resource discovery, error handling, and more, enabling interoperability between different implementations.