Model Context
Standardizes client-server communication, allowing large language models to access server-defined tools and resources.
About
The Model Context Protocol (MCP) establishes a standardized client-server architecture for artificial intelligence models, particularly Large Language Models (LLMs), to effectively communicate with and utilize server-side assets. It provides a structured framework for defining and exposing tools, resources, prompts, and sampling mechanisms, allowing LLMs to extend their capabilities by interacting with external functionalities and data sources in a controlled environment.
Key Features
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- Standardized client-server architecture for LLM interaction
- Support for dynamic parameter input for functions and data access
- VS Code integration for server management and tool access
- Integration of server-defined tools, resources, prompts, and sampling
- Interactive command-line interface (CLI) client for server interaction
Use Cases
- Enabling LLMs to retrieve and utilize external data resources
- Providing structured prompts and sampling for refined LLM outputs
- Allowing LLMs to execute external tools and functions
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