Andreas Hilbig
bbf7357e93
This commit introduces several improvements to the project's documentation, roadmap, and AI agent integration (MCP). Key changes: - Created and styled roadmap.md to track project milestones and future plans. - Updated .junie/guidelines.md with strict documentation style standards. - Automated GraphQL schema concatenation for the MCP server using a schema-gen init-container. - Updated MCP setup recipes in cookbook.md and mcp.md to reflect the new automation. - Added .ai/mcp/mcp.json for connecting to existing MCP services via HTTP. - Improved development workflow by updating package.json to watch .graphql files. - Cleaned up the root directory by moving schema.graphql to .gitignore and removing redundant files. - Standardized visual style and formatting across all markdown files.
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How-To Guides
This directory contains detailed guides on how to use and extend the Zabbix GraphQL API.
Available Guides
🍳 Cookbook
Practical, step-by-step recipes for common tasks, designed for both humans and AI-based test generation.
📊 Schema and Schema Extension
Learn about the GraphQL schema structure, how Zabbix entities map to GraphQL types, and how to use the dynamic schema extension system.
🗂️ Hierarchical Data Mapping
Understand how the API automatically maps flat Zabbix item keys into nested GraphQL objects using hierarchical resolvers and type hinting.
🔐 Roles and Permissions Extension
Discover how the permission system works, how to define permission levels using Zabbix template groups, and how to query user permissions.
🛠️ Technical Maintenance
Guide on code generation (GraphQL Codegen), running Jest tests, and local Docker builds.
🤖 MCP & Agent Integration
Discover how to integrate with the Model Context Protocol (MCP) to enable LLMs and autonomous agents to interact with Zabbix efficiently.
🔍 Additional Resources
- Sample Queries: Categorized list of practical GraphQL operation examples.
- Main README: Technical reference, configuration, and environment setup.