obsidian-rag
Provides semantic search over an Obsidian vault, enabling query-by-meaning across markdown notes.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@obsidian-ragfind notes about project architecture"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Obsidian RAG — Semantic Note Search
Local semantic search for your Obsidian vault, powered by BAAI/bge-m3 embeddings and ChromaDB.
Features
Semantic search — find notes by meaning, not just keywords
Markdown-aware chunking — splits by heading hierarchy for better context
Apple Silicon acceleration — MPS support for M-series Macs
Multiple interfaces — CLI, REST API, and MCP server (for Claude/Cursor)
Multilingual — full Chinese-English support via bge-m3
Related MCP server: Obsidian RAG MCP Server
Quick Start
# Install
pip install -e .
# Index your vault
export OBSIDIAN_VAULT_PATH="/path/to/your/vault"
python -m obsidian_rag index "$OBSIDIAN_VAULT_PATH" --full
# Search
python -m obsidian_rag search "your question"
# Start API server (for web UI or integrations)
python -m obsidian_rag apiArchitecture
Obsidian vault (.md files)
→ chunker.py: split by Markdown headings
→ embeddings.py: BAAI/bge-m3 (MPS accelerated)
→ ChromaDB: cosine similarity vector store
→ Interfaces:
├── CLI: python -m obsidian_rag search "query"
├── REST API: FastAPI on :8787
└── MCP: Claude Code / Cursor integrationTech Stack
Component | Choice |
Embedding model | BAAI/bge-m3 (1024d, multilingual) |
Vector DB | ChromaDB (local, cosine space) |
API | FastAPI + Uvicorn |
AI integration | MCP (Model Context Protocol) |
MCP Configuration
For Claude Code (.mcp.json):
{
"mcpServers": {
"obsidian-rag": {
"command": "python",
"args": ["-m", "obsidian_rag.server"],
"env": {
"OBSIDIAN_VAULT_PATH": "/path/to/your/vault"
}
}
}
}This server cannot be installed
Maintenance
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Related MCP Servers
- Flicense-qualityDmaintenanceProvides AI assistants with full-text search access to your Obsidian vault, allowing them to query, retrieve, and analyze notes through the Model Context Protocol.3
- Flicense-quality-maintenanceEnables semantic search and content retrieval from local Obsidian vaults through the Model Context Protocol. It allows AI assistants to query notes by meaning, filter by tags, and access full note content for enhanced knowledge integration.
- Alicense-qualityDmaintenanceEnables AI assistants to interact with Obsidian vaults through vector search, vault indexing, and file monitoring. It provides a standardized interface for searching and managing markdown-based personal knowledge management data within the Model Context Protocol.6,1041MIT
- Flicense-qualityAmaintenanceEnables semantic search and note management for Obsidian vaults via the Model Context Protocol, allowing LLMs to search, read, and index notes, PDFs, and web pages locally.
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