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metamind-vault-rag

by Nikitzu

metamind-vault-rag

マークダウンのディレクトリ向けの検索エンジンです。ファイルを監視し、インクリメンタルにインデックス化し、それらに対するハイブリッド検索クエリに応答します。

ベクトルは sqlite-vec に、キーワードは SQLite FTS5 に格納され、両者は相互ランク融合によって融合されます。埋め込みは fastembed の ONNX モデルを通じてプロセス内で実行されるため、立ち上げるサーバーも保持する API キーもありません。オプションのクロスエンコーダーによる再スコア層は、rerank エクストラを通じて利用できます。

インストール

uv tool install metamind-vault-rag

Related MCP server: mnemonic

エントリーポイント

コマンド

目的

metamind-vault-rag-watcher

ディレクトリを監視して変更をインデックス化

metamind-vault-rag-indexer

ワンショットの完全再インデックス

metamind-vault-rag-http

ループバック HTTP 検索 API

metamind-vault-rag-server

stdio MCP サーバー

metamind-vault-rag-doctor

環境とインデックスの診断

設定

変数

意味

VAULT_PATH

インデックス化するディレクトリ

VAULT_COLLECTION

コレクション名。インデックスファイルのスコープを定義します

VAULT_HTTP_PORT

ループバック検索 API のポート

VAULT_STATE_DIR

インデックス、キャッシュ、ログが書き込まれる場所。デフォルトは ~/.vault-rag

インデックスはステートディレクトリに書き込まれ、コレクション名にちなんで命名され、コーパス内には決して配置されません。異なるコレクションまたは異なるステートディレクトリを指す2つのクライアントは、互いの存在を知ることなく1つのマシン上で共存できます。

利用者

サービスを実行せずに検索を必要とする任意のクライアントによってインストールされます。エンジンは誰が問い合わせているかについて意見を持ちません。出力にクライアント名を一切記載せず、環境変数はすべて VAULT_ プレフィックスが付き、ステートディレクトリの外には何も書き込みません。

開発

uv run --extra dev pytest

クライアントは、uv tool install --from /path/to/this/repo metamind-vault-rag を使用して、リリースの代わりに作業コピーを指すことができます。

ライセンス

MIT

Available Tools

3 tools
search_vaultC

Semantic search over the Obsidian Knowledge vault.

ParametersJSON Schema
NameRequiredDescriptionDefault
kNo
queryYes

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

C2.1/5.0
Behavior2/5

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

Annotations are absent, so the description should fully disclose behavioral aspects. It merely states 'semantic search' – which implies a read operation but does not explicitly state side effects, resource constraints, or result handling. No details on output stability, rate limits, or side effects are given. Minimal transparency.

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

Conciseness2/5

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

The description is a single sentence, which is concise. However, it is under-specified: it lacks necessary detail for an agent to use the tool effectively. The brevity is not a virtue because it omits critical information, making it more of an under-specification than a well-structured concise entry.

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

Completeness2/5

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

The tool has two parameters and an output schema, but the description gives no information about return format, pagination, or semantics. Since annotations are missing, the description must bear the burden of explaining expected behavior. It fails to provide enough context to use the tool safely, especially for a semantic search that could have variable behavior.

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

Parameters1/5

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

Schema description coverage is 0%, so the description is the only source of parameter meaning. The description does not mention 'query' or 'k' at all. The schema lists 'k' with a default but no description, and 'query' without context. This is a complete failure to provide any parameter semantics in the description.

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

Purpose3/5

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

The description states it performs 'semantic search' over the vault, which clearly identifies the action and resource. However, it does not differentiate from sibling tools like 'related_notes' or 'expand_search' – the term 'semantic' hints at a method but not why this one is distinct. Purpose is clear but not enriched with scope or contrast.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus the siblings. The description only states what it does, not when it is the right choice. There is no mention of use cases, exclusions, or alternative recommendations.

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

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 3 tool updatesv0.10.1
    • First observedexpand_search
    • First observedrelated_notes
    • First observedsearch_vault

TDQS

C2.7/5.0

Scored across 3 tools

Disambiguation5/5

Each tool has a clearly distinct purpose: semantic search, finding related notes, and expanding search via wikilinks. There is no overlap or ambiguity.

Naming Consistency4/5

All tools use snake_case and follow a verb-like pattern, but 'related_notes' uses an adjective rather than a verb, creating minor inconsistency with the verb_noun style of the other two.

Tool Count5/5

With only 3 tools, the set is minimal but well-scoped for the server's focus on vault search and navigation. It avoids superfluous tools while covering essential actions.

Completeness5/5

The server covers the core needs of a RAG vault assistant: searching semantically, exploring relationships, and expanding through linked notes. This is a complete set for its intended purpose.

Maintenance

ActivitySlowing
ResponsivenessNo issues

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