Search markdown knowledge bases efficiently using qmd. Use this when searching Obsidian vaults or markdown collections to find relevant content with minimal token usage.
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Search markdown knowledge bases efficiently using qmd, a local indexing tool that uses BM25 + vector embeddings to return only relevant snippets instead of full files.
qmd search "your query" --collection <name>
Fast, accurate keyword-based search. Best for specific terms or phrases.
qmd vsearch "your query" --collection <name>
Semantic similarity search. Best for conceptual queries where exact words may vary.
qmd hybrid "your query" --collection <name>
Combines both approaches with LLM reranking. Most thorough but often overkill.
Check if collection exists:
qmd collection list
Search the collection:
# For specific terms qmd search "api authentication" --collection notesFor conceptual queries
qmd vsearch "how to handle errors gracefully" --collection notes
Read results: qmd returns relevant snippets with file paths and context
# Install qmd bun install -g https://github.com/tobi/qmdAdd a collection (e.g., Obsidian vault)
qmd collection add ~/path/to/vault --name notes
Generate embeddings for vector search
qmd embed --collection notes
/qmd api authentication # BM25 search for "api authentication" /qmd how to handle errors --semantic # Vector search for conceptual query /qmd --setup # Guide through initial setup
qmd searchqmd vsearchqmd embed$ARGUMENTS--semanticqmd vsearchqmd search--setup--collection <name>$ARGUMENTSwhich qmdNo automatic installation available. Please visit the source repository for installation instructions.
View Installation Instructions
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