What are the prerequisites?
Python 3.12 or later, Docker and Docker Compose (for containerized use), and optionally `uv`.
@pmmvr
Basic information
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
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"obsidian-index-service": {
"command": "uv",
"args": [
"venv"
]
}
}
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
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.

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

Model Context Protocol Servers

AI agents start every session with amnesia — you re-explain the project, repeat your preferences, and correct the same mistakes over and over. PLUR gives them a memory that persists. Your agent's corrections, preference

Shared memory for AI coding agents. Claude Code, Cursor and Codex read your project's decisions, lessons and tasks before they act.
Comments