Server Core

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This project offers a Proof of Concept (POC) implementation of a Model Context Protocol (MCP) server, designed in Python to empower AI assistants and other MCP clients with a rich set of tools and resources. Following a modular architecture, it cleanly separates client, transport, server core, tool implementations, and resource providers. This setup ensures extensibility and maintainability, allowing seamless integration with external services and robust handling of various requests, from listing available tools to executing complex operations and fetching structured resources.

Características Principales

• Full type safety enforced with Pydantic models for reliable data validation
• High-performance asynchronous operations powered by uvloop
• Comprehensive suite of example tools covering calculations, URL fetching, system info, data processing, and file operations
• Modern Python Stack with async/await patterns and Python 3.10+
• Flexible resource management supporting file-based and configuration-based resources
• 0 GitHub stars

Casos de Uso

• Integrating AI assistants with external system tools and data sources
• Providing on-demand mathematical calculation and data processing capabilities to intelligent agents
• Enabling AI clients to fetch real-time system information or interact with local files and web APIs