tegwick
2dd1704e51
Adds a complete GraphQL API for querying MarkiTect database content including: CORE FEATURES: - Type-safe GraphQL schema with comprehensive field definitions - Full database access: markdown files, schemas, ASTs, and metadata - Advanced search capabilities with relevance scoring - Pagination support for efficient data access - Real-time schema introspection and development tools IMPLEMENTATION: - GraphQL schema definition with 6 core types (MarkdownFile, Schema, AST, etc.) - Complete resolver implementation with database integration - Flask-based GraphQL server with CORS support - GraphQL Playground for interactive development - Health check and schema introspection endpoints CLI INTEGRATION: - graphql-serve: Start GraphQL server with customizable options - graphql-query: Execute queries from command line (local/remote) - graphql-schema: Retrieve schema definition in SDL/JSON format - graphql-examples: Comprehensive usage examples and documentation API FEATURES: - Single item queries (by ID or filename) - List queries with filtering and pagination - Full-text search across files and schemas - Database statistics and analytics - AST querying with JSONPath expressions - Computed fields (word count, line count, etc.) TESTING: - Comprehensive test suite with 38 passing tests - Unit tests for schema, resolvers, server, and client - Integration tests for query execution - Error handling and edge case coverage - Mock and fixture support for isolated testing DOCUMENTATION: - Complete API documentation with examples - Usage guide for all CLI commands - Programming examples in Python and JavaScript - Performance optimization guidelines - Troubleshooting and security considerations The GraphQL interface enables developers to build rich applications on top of MarkiTect data with flexible, efficient querying capabilities. 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
MarkiTect - Advanced Markdown Engine
Your Markdown, Redefined.
MarkiTect transforms markdown from plain text into intelligent, structured data with performance optimization, schema validation, and relational querying capabilities. Stop treating documentation as text files—start managing it as a database.
Key Features:
- Lightning Performance: 60-85% faster document processing through intelligent AST caching
- Schema Validation: Enforce document structure and consistency
- Database Integration: Query markdown content with SQL-like operations
- CLI Tools: Complete command-line interface for automation and workflows
📚 Documentation
Quick Start: Getting Started · Command Reference
Architecture: Caching System · Performance Philosophy
Development: TDD Workflow · Contributing
Project Status: Current Status · Roadmap · Next Actions