Overview
Features
Atomic Notes with Unique IDs and Metadata
One concept per note with a unique ID, title, body, summary, and timestamped metadata for precise linking.
Bi-directional Linking and Knowledge Graph
Typed relationships between notes form a navigable knowledge graph to enable concept connections.
AI-Powered CEQRC Workflow
Capture → Explain → Question → Refine → Connect pipeline to guide understanding and relationships, powered by AI.
Auto-Summarization and Metadata Suggestions
AI-generated concise summaries and suggested titles, tags, and relationships to surface key insights.
YAML Frontmatter + Markdown Storage
Notes stored as Markdown with rich YAML frontmatter, serving as the source of truth and metadata container.
Full-Text and Semantic Search
SQLite FTS5 index supports full-text search with proximity, phrase queries, and tag-based filtering.
Multiple Interfaces
CLI, REST API, Streamlit UI, and MCP Server provide broad access for use and automation.
MCP Integration and Tools
Expose to AI assistants via MCP; toolset includes zk_create_note, zk_search_notes, zk_get_note, zk_run_ceqrc_workflow, zk_suggest_links, zk_create_link, zk_generate_summary.
Who Is This For?
- Researchers:Capture research notes, link concepts, and refine ideas with AI workflows.
- Students:Summarize materials, generate study questions, and build connected notes for exam preparation.
- Knowledge workers:Organize information, meeting notes, and project knowledge with AI-assisted linking.
- AI integrators:Expose knowledge base to external AI assistants via MCP for automation.




