What are the prerequisites?
Python 3.12 or later, Docker and Docker Compose (for containerized use), and optionally `uv`.
@pmmvr
基本情報
A service that monitors an Obsidian vault for file changes (new, modified, or deleted Markdown files) and indexes each note’s metadata and content into an SQLite database, exposing it for e.g. an MCP-server
以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。
{
"mcpServers": {
"obsidian-index-service": {
"command": "uv",
"args": [
"venv"
]
}
}
}ツール一覧はまだありません
この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。
ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。
Obsidian Index Service monitors an Obsidian vault directory and indexes Markdown files—metadata and full content—into an SQLite database. It tracks file changes (create, modify, delete) and stores path, title, tags, timestamps, content, and processing status. It is intended as an agnostic note indexer and potential sync tool.
Set environment variables OBSIDIAN_VAULT_PATH and DB_PATH, or pass --vault-path and --db-path command-line options. Run locally with python main.py or uv run python main.py. Use --scan-only for a one-time scan. For Docker, run docker-compose up -d to mount the vault and expose the database.
Python 3.12 or later, Docker and Docker Compose (for containerized use), and optionally `uv`.
Data is stored in an SQLite database at the path specified by `DB_PATH` (default `/data/notes.sqlite` in Docker). The database is mounted as a Docker volume.
SQLite is run in Write-Ahead Logging (WAL) mode. Other services can mount the same volume read-only (e.g., `/data:ro`) and safely query the database while Obsidian Index Service writes to it.
By default it watches the vault continuously; use `--scan-only` to index once and exit.
Path (unique identifier), title (from filename), parent folders (relative to vault root), tags (from YAML frontmatter), created/modified timestamps, full content, processing status, and error message if processing fails.

Exact, shared memory for AI agents: a hierarchical database where totals always add up, every write is attributed to the agent and person behind it, and any figure traces back to its source file. Agents create databases,
Groundwork: company memory for your AI tools. Docs public. Source closed. Public proof needs no account.

Mess in, magic out: pour in your D&D and TTRPG notes and LoreKeeper keeps them as a private store for your world. Ask Claude or ChatGPT about it, or build a sourcebook.

MCP connector for Snipara, the Project Brain for AI coding agents

Personal context for every AI: search, read, and write back to your private Markdown library of articles, threads, PDFs, notes, and captured ChatGPT/Claude/Gemini/Grok conversations. Remote server, OAuth 2.1 paste-and-au
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