obsidian-mcp

obsidian-mcp

Exposes an Obsidian vault with full-text and semantic search, and Anki-style spaced repetition active recall.

Category
Visit Server

README

obsidian-mcp

A TypeScript MCP server that exposes your Obsidian vault to any MCP-compatible client (Claude Desktop, Claude Code, etc.) with full-text + semantic search and Anki-style spaced-repetition active recall.


Features

Capability Tools
Vault reading list_notes, get_note, get_recent_notes, get_backlinks, get_vault_stats
Search search_notes (hybrid FTS5 + semantic), get_notes_by_topic
Active recall cross_question, get_due_questions, submit_review, get_topic_mastery
Question store add_questions, list_questions, delete_question
  • Local embeddingsall-MiniLM-L6-v2 via @xenova/transformers. No note content leaves the machine.
  • SQLite — FTS5 full-text index + embedding vectors (pure-JS cosine similarity fallback if sqlite-vec is unavailable).
  • Git sync — vault mirrored from MacBook → EC2 via git; health status reported in get_vault_stats.
  • SM-2 scheduler — classic SuperMemo-2 algorithm for spaced repetition.
  • stdio + HTTP/SSE transports — stdio for Claude Desktop, SSE for remote EC2 access.

Quick Start (local / Claude Desktop)

# 1. Clone and install
git clone https://github.com/YOUR_USERNAME/obsidian-mcp.git
cd obsidian-mcp
npm install

# If on Node 25+ (no prebuilt better-sqlite3 binary yet), build from source:
npm run rebuild:sqlite

# 2. Build
npm run build

# 3. Copy and edit .env
cp .env.example .env
# Set VAULT_PATH to your Obsidian vault directory

# 4. Run (stdio mode)
VAULT_PATH=/path/to/your/vault npm start

Claude Desktop config

Add to ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "obsidian": {
      "command": "node",
      "args": ["/absolute/path/to/obsidian-mcp/dist/index.js"],
      "env": {
        "VAULT_PATH": "/absolute/path/to/your/vault"
      }
    }
  }
}

Environment Variables

Variable Required Default Description
VAULT_PATH Absolute path to Obsidian vault
TRANSPORT No stdio stdio or http
PORT No 3000 HTTP port (when TRANSPORT=http)
MCP_AUTH_TOKEN No* Bearer token for HTTP auth (*required in production)
DB_PATH No ./data/obsidian-mcp.db SQLite database path
LOG_LEVEL No info debug | info | warn | error
TRANSFORMERS_CACHE No ~/.cache/huggingface Where to cache the embedding model

EC2 Deployment

1. Set up EC2 → GitHub SSH access

# On EC2: generate a deploy key (read-only) for the vault repo
ssh-keygen -t ed25519 -C "ec2-vault-deploy" -f ~/.ssh/vault_deploy_key -N ""
cat ~/.ssh/vault_deploy_key.pub
# Add the public key to your vault repo as a read-only deploy key on GitHub

2. Run the bootstrap script

# On EC2 (as ec2-user):
export REPO_URL="https://github.com/YOUR_USERNAME/obsidian-mcp.git"
export VAULT_REPO="git@github.com:YOUR_USERNAME/obsidian-vault.git"
bash scripts/setup-ec2.sh

The script:

  • Installs Node.js 20 via nvm
  • Clones vault + server repos
  • Builds TypeScript
  • Creates .env with a randomly generated MCP_AUTH_TOKEN
  • Installs and starts all systemd units (MCP server + 5-min vault sync timer)

3. Set up nginx + TLS

sudo apt install -y nginx certbot python3-certbot-nginx

# Copy config and replace domain
sudo cp nginx/obsidian-mcp.conf /etc/nginx/sites-available/obsidian-mcp
sudo ln -s /etc/nginx/sites-available/obsidian-mcp /etc/nginx/sites-enabled/
# Edit: sed -i 's/mcp.yourdomain.com/your.actual.domain/g' /etc/nginx/sites-available/obsidian-mcp

sudo certbot --nginx -d your.actual.domain
sudo systemctl reload nginx

4. Mac → EC2 vault sync (auto git push)

# Edit VAULT_DIR in the plist first
nano launchd/com.obsidian.sync.plist

# Install
cp launchd/com.obsidian.sync.plist ~/Library/LaunchAgents/
launchctl load ~/Library/LaunchAgents/com.obsidian.sync.plist

# Verify
launchctl list | grep obsidian
tail -f /tmp/obsidian-sync.log

5. Claude Desktop → EC2 (HTTP/SSE)

{
  "mcpServers": {
    "obsidian-remote": {
      "url": "https://your.actual.domain/sse",
      "headers": {
        "Authorization": "Bearer YOUR_MCP_AUTH_TOKEN"
      }
    }
  }
}

Active Recall Workflow

User: "Quiz me on machine learning"
  → cross_question(topic="machine learning", depth="medium")
  ← Server returns: relevant notes + due questions

Claude reads notes, asks due questions first, then generates new ones
  → submit_review(question_id=42, grade="good")
  ← SM-2 schedules next review in N days

  → add_questions(note_path="ML/Backprop.md", questions=[...])
  ← Stored for future review sessions

User: "How am I doing on ML?"
  → get_topic_mastery(topic="machine learning")
  ← Stats: 23 questions, 18 reviewed, avg ease 2.3, 3 weak areas

MCP Tools Reference

Vault Tools

Tool Description
list_notes List notes, filter by tag and/or folder
get_note Get full note content by path or title
search_notes Hybrid FTS + semantic search (mode: hybrid/fulltext/semantic)
get_notes_by_topic Semantic + tag search for a topic
get_backlinks Find notes linking to a note via [[wikilinks]]
get_recent_notes N most recently modified notes
get_vault_stats Note count, tags, folders, git sync status

Review Tools

Tool Description
cross_question Quiz-me entry point: returns notes + due questions for a topic
get_due_questions Questions due for review today (SM-2 scheduled)
submit_review Record grade (again/hard/good/easy), update SM-2 schedule
get_topic_mastery Aggregate stats: reviewed, overdue, avg ease, weak areas

Question Tools

Tool Description
add_questions Store LLM-generated questions for a note
list_questions List all questions, filtered by note path
delete_question Remove a question from the review queue

Architecture

obsidian-mcp/
├── src/
│   ├── index.ts              # Entry point (stdio / HTTP)
│   ├── server.ts             # McpServer factory
│   ├── db/
│   │   ├── schema.ts         # SQLite init (FTS5, embeddings, SM-2 state)
│   │   └── sm2.ts            # SM-2 algorithm
│   ├── embeddings/
│   │   └── model.ts          # @xenova/transformers wrapper + cosine fallback
│   ├── vault/
│   │   ├── parser.ts         # Markdown → Note (gray-matter, wikilinks, tags)
│   │   ├── indexer.ts        # Full scan + chokidar file watcher
│   │   └── search.ts         # FTS5 + semantic + hybrid + topic search
│   ├── tools/
│   │   ├── vault.ts          # Vault reading tools
│   │   ├── questions.ts      # Question CRUD tools
│   │   └── review.ts         # Active recall + SM-2 tools
│   └── transport/
│       └── http.ts           # Express SSE + bearer auth
├── systemd/                  # EC2 systemd units + timer
├── launchd/                  # Mac launchd plist (auto git push)
├── nginx/                    # nginx reverse proxy config
└── scripts/
    └── setup-ec2.sh          # EC2 one-shot bootstrap

Notes on sqlite-vec

The server automatically attempts to load the sqlite-vec native extension for vector operations. If it fails to load (e.g. on some Apple Silicon configs without Rosetta), it falls back seamlessly to a pure-JS cosine similarity implementation. This fallback works well for vaults up to ~5,000 notes; for larger vaults, ensure sqlite-vec is available.

# Test if sqlite-vec loads on your system
node -e "require('sqlite-vec')"

Backups

The SQLite DB (data/obsidian-mcp.db) holds your review state — this is the only data that can't be reconstructed from the vault. Back it up:

# Manual backup
cp data/obsidian-mcp.db "data/obsidian-mcp-$(date +%Y%m%d).db"

# Cron backup on EC2 (add to crontab)
0 3 * * * sqlite3 /home/ec2-user/obsidian-mcp/data/obsidian-mcp.db ".backup '/home/ec2-user/backups/obsidian-mcp-$(date +\%Y\%m\%d).db'"

License

MIT

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured