Find passages in the knowledge base by meaning rather than keywords.

Use when the question is conceptual or the user's wording is unlikely to match the note's wording verbatim — "how do I handle X", "what did I decide about Y". For exact strings, literal identifiers, or filenames, prefer knowledge-mcp's search_knowledge instead.

Returns the best-matching chunks with their document path, section breadcrumb, and similarity score. Read the full note via knowledge-mcp's read_knowledge using the returned path.

List documents carrying a frontmatter tag, e.g. "hermes" or "homelab".

Use for tag-based navigation — "what notes are tagged X". Call list_tags first if unsure which tags exist. Returns paths; read content via knowledge-mcp's read_knowledge.

List every tag in the corpus with how many documents use it.

Use to discover the corpus's own vocabulary before calling documents_by_tag.

Show what a specific note is about: its tags, its wikilinks in and out, and (once the semantic pass has run) the entities it mentions.

Use when you already know which note you care about and want its neighbourhood — "what does this note connect to". path is relative to the knowledge base root, e.g. "projects/my-project.md".

Find notes covering similar ground to a given note, by embedding similarity rather than by explicit links.

Use to surface related material the wikilinks miss — near-duplicates, or an older note on the same topic. Complements entities_in_document, which only sees links you wrote by hand.

Report what the graph currently contains — node and edge counts per type.

Use to check which extraction stages have run before trusting a query that depends on them.