mcp-glpi vs python-sdk
mcp-glpi: MCP Server for GLPI exposes GLPI's IT Service Management functionalities, including tickets, assets, and statistics, to AI assistants via a structured API. It offers solid foundations with robust error handling, real multi-criteria search, and dynamic field mapping to ensure compatibility and ease of use for LLMs.; python-sdk: The MCP Python SDK provides a robust implementation of the Model Context Protocol, enabling developers to build secure, standardized servers that expose data and functionality to LLM applications. It also includes a client library for connecting to any MCP server, supporting various standard transports like stdio, Streamable HTTP, and SSE.
TL;DR
Automating IT service ticket management, including creation, updates, and assignments.
- You want the official, MIT-licensed reference Python SDK maintained directly by the Model Context Protocol project.
- You need full low-level control over MCP primitives (resources, prompts, tools, sampling) and standard transports (stdio, SSE, Streamable HTTP).
- You want higher-level conveniences like automatic client composition or less decorator boilerplate; FastMCP wraps the protocol with extra ergonomics.
- You are exposing an existing GraphQL or FastAPI backend where a gateway or adapter (Grafbase or FastAPI-MCP) requires no manual tool code.
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