OpenZIM MCP Server is a modern, secure, high-performance MCP (Model Context Protocol) server designed to transform static ZIM archives into dynamic knowledge engines for AI models. It enables offline access to large knowledge bases (e.g., Wikipedia) by providing structured, namespace-based retrieval, intelligent search, and robust content processing. The server supports dual mode operation: Simple mode with a single intelligent tool for natural language queries and Advanced mode exposing 15 specialized MCP tools for deeper control. It features security-first validation, path traversal protection, and a modular architecture with dependency injection, full type annotations, and configurable settings. It offers smart retrieval, automatic fallback from direct access to search-based retrieval, and cached operations to prevent timeouts on massive archives. It includes multi-server instance management with conflict detection and stale-instance cleanup to ensure safe operation in multi-instance environments. The project emphasizes testing (90%+ coverage), observability (structured logging, health monitoring), and extensive configuration via environment variables. It integrates with the zim-testing-suite for comprehensive testing and supports ZIM metadata queries, article structure extraction, and link extraction to empower LLMs with offline knowledge access.