Sample
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Exposes data, tools, and templates to large language model applications via the Model Context Protocol.
About
The Model Context Protocol (MCP) creates a bridge between large language model (LLM) applications and external context sources. This sample demonstrates how to build a functional MCP server using Python's MCP SDK. It enables the exposure of various components to LLMs: data provision through resources, action execution via tools, and template management using prompts, allowing LLMs to dynamically interact with external systems and information.
Key Features
- Utilizes a Python SDK for straightforward MCP server creation
- Facilitates modularization of LLM interactions into distinct components
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- Exposes data (resources), actions (tools), and templates (prompts) to LLMs
- Supports dynamic capability advertising and updates for server features
- Provides a built-in development inspector for interactive testing and debugging
Use Cases
- Integrating custom calculations or external API calls for LLMs to execute
- Providing dynamic, context-specific data or file content to LLM applications
- Creating reusable interaction templates and command shortcuts for LLM-driven workflows
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