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artificemachine

Obsidian Semantic MCP

search_vault

Search across your Obsidian vaults using hybrid, semantic, or keyword modes to retrieve context, notes, and past decisions.

Instructions

Search across your Obsidian vault(s). Three modes: 'hybrid' (default) combines semantic meaning with keyword matching for best results; 'semantic' searches by meaning only; 'keyword' matches exact words using full-text search. Use this to retrieve context, past decisions, notes, or research from the vault.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNoSearch mode: 'hybrid' (default) combines semantic + keyword; 'semantic' uses vector similarity only; 'keyword' uses full-text search only.hybrid
limitNoNumber of results to return (default: 5, max: 20)
queryYesNatural language search query
vaultNoFilter results to a specific vault by its name (basename of vault path). Omit to search all vaults.
graph_expandNoFollow wikilinks from top results to surface connected notes that didn't rank semantically. Useful for discovering missed connections.
min_similarityNoMinimum similarity score (0.0–1.0). Results below this threshold are excluded. Default: 0.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It transparently explains the three search modes, default behavior (hybrid), the graph_expand feature, and similarity threshold. It does not mention error handling or performance, but for a read-only search tool the description is sufficiently revealing.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences long, front-loading the core purpose, then efficiently expanding on modes and use cases. No redundant or wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema and no annotations, the description covers the essential functionality, modes, and typical usage. It does not specify the return format or error conditions, but for a search tool the description is adequate for an agent to select and invoke it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents each parameter. The description adds context for modes and the graph_expand feature (e.g., 'Useful for discovering missed connections'), but does not significantly augment the schema's own descriptions. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it searches across Obsidian vaults, describes three distinct modes (hybrid, semantic, keyword), and lists use cases (retrieve context, past decisions, notes, research). It distinguishes from sibling tools like simple_search and get_note_connections by being more comprehensive.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description says 'Use this to retrieve context, past decisions, notes, or research' which implies appropriate usage. It does not explicitly state when not to use it or compare to siblings, but the context signals show it is more powerful than simple_search, so some differentiation is possible.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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