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Obsidian Semantic Search

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Read-only semantic search MCP server for Obsidian vaults using local Ollama embeddings.

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Описание

Read-only semantic search MCP server for Obsidian vaults using local Ollama embeddings.

README

Obsidian Semantic Search MCP

Read-only semantic retrieval for agents that need to find the right Obsidian note without write access.

npm MCP Registry License Node.js

한국어 · Quick Start · Why This Exists · How It Works


Your Obsidian vault is useful only if your agent can find the right note.

Keyword search misses context. Full write-capable Obsidian MCP servers expose more power than a retrieval agent needs. Obsidian plugins are great inside Obsidian, but they are not always the right boundary for Codex, Claude Desktop, Cursor, or any other MCP client.

This project is the narrow version:

local Obsidian vault -> read-only scanner -> local SQLite index -> MCP search/read tools

No note writes. No cloud embeddings. No Obsidian plugin runtime. No sync service.

Local, read-only pipeline: Obsidian vault to scanner to chunker to Ollama embeddings to SQLite index, queried by an MCP client via search_notes and read_note

Status: 0.2.1 early preview. The server is usable today, but ranking behavior and tool schemas may change before 1.0.

What You Get

Need What this server does
Find the note an agent should read Hybrid semantic + keyword search over Markdown notes
Keep the vault safe Exposes search/read/index/status only; no write, patch, move, rename, or delete tools
Stay local-first Uses Ollama embeddings and stores the index on your machine
Make results agent-friendly Returns file-level matches with headings, snippets, and line ranges
Avoid plugin state Reads the vault directly from the filesystem; Obsidian does not need to be running

Example result shape:

{
  "path": "02_Projects/RealtimeAPI/05_Interview_QA.md",
  "title": "Interview Q&A",
  "score": 0.7431,
  "matched_sections": [
    {
      "heading": "Level 4 > Redis Lua atomicity",
      "lines": [266, 305],
      "reason": "semantic=1, keyword=0.5565, metadata=0.6"
    }
  ]
}

Quick Start

Requirements:

  • Node.js >= 24
  • Ollama
  • An Obsidian vault
  • An MCP client such as Codex, Claude Desktop, Cursor, or another stdio MCP client

Install the embedding model:

ollama pull bge-m3
curl http://localhost:11434/api/tags

Print setup guidance:

npx -y --package @dalecb/obsidian-semantic-mcp obsidian-semantic-mcp-setup

Codex Setup

Add this to ~/.codex/config.toml:

[mcp_servers.obsidian_semantic]
command = "npx"
args = ["-y", "@dalecb/obsidian-semantic-mcp"]

[mcp_servers.obsidian_semantic.env]
OBSIDIAN_VAULT_ROOT = "/path/to/your/Obsidian Vault"
OBSIDIAN_SEMANTIC_MCP_HOME = "/Users/you/.obsidian-semantic-mcp"
OBSIDIAN_EMBED_MODEL = "bge-m3"
OBSIDIAN_SEMANTIC_STARTUP_INDEX = "false"

Restart Codex, then run:

obsidian_semantic.index_status
obsidian_semantic.index_vault { "mode": "incremental" }
obsidian_semantic.search_notes { "query": "Redis Lua atomicity", "limit": 5 }

JSON MCP Clients

Claude Desktop, Cursor, and other JSON-style MCP clients can use:

{
  "mcpServers": {
    "obsidian_semantic": {
      "command": "npx",
      "args": ["-y", "@dalecb/obsidian-semantic-mcp"],
      "env": {
        "OBSIDIAN_VAULT_ROOT": "/path/to/your/Obsidian Vault",
        "OBSIDIAN_SEMANTIC_MCP_HOME": "/Users/you/.obsidian-semantic-mcp",
        "OBSIDIAN_EMBED_MODEL": "bge-m3",
        "OBSIDIAN_SEMANTIC_STARTUP_INDEX": "false"
      }
    }
  }
}

Why This Exists

This isn't aiming to be the most powerful Obsidian automation server. It aims to be the safest retrieval tool you can hand an agent.

Here's how it stacks up against the two tools it usually comes down to — a full-permission Obsidian MCP server (Local REST API based) and GBrain (a broader knowledge-compilation platform):

This project Full-permission Obsidian MCP GBrain
Access model Read-only: search / read / index Read + write + edit + delete Read + write; compiles notes into its own model
Touches your vault Never Yes Yes — restructures content
Obsidian must run No — reads files directly Yes — needs the REST API plugin No
Extra runtime None Obsidian + plugin Standalone platform
Embeddings & data Local Ollama; nothing leaves the machine Local API; embeddings vary by setup Built-in pipeline; optional sync
Storage One SQLite file you can delete and rebuild Plugin-managed Its own store / migration
Best for A small read-only retrieval boundary for agents Full vault automation and editing Building a compiled knowledge base across sources

That trade is on purpose: give up writing, editing, and running inside Obsidian, and you get fewer moving parts and a smaller blast radius in return.

Use this if your agent should answer:

  • "Which note explains this project decision?"
  • "Find the file where I wrote about idempotency payload mismatch."
  • "Show me the career notes related to this interview topic."
  • "Search my vault, but do not mutate it."

Do not use this if you want an Obsidian UI plugin, automatic note generation, or write-capable vault automation.

Tools

index_status

Returns index metadata and safety settings.

index_vault

Builds or updates the external SQLite index.

{ "mode": "incremental" }

Specific files:

{
  "mode": "incremental",
  "paths": ["02_Projects/My Note.md"]
}

search_notes

Searches notes with hybrid semantic and keyword ranking.

{
  "query": "live coding notes",
  "limit": 8,
  "mode": "hybrid"
}

Modes:

  • hybrid: semantic vector + SQLite FTS5 + metadata boosts
  • semantic: vector-first search
  • keyword: FTS5 keyword search without embedding the query

read_note

Reads a note or line range by vault-relative path.

{
  "path": "02_Projects/My Note.md",
  "start_line": 10,
  "end_line": 40
}

How It Works

index_vault
  -> scan Markdown files under OBSIDIAN_VAULT_ROOT
  -> block denied paths and symlink escapes
  -> split notes by Markdown headings
  -> create one summary chunk per file
  -> embed chunks with Ollama bge-m3
  -> store notes, chunks, FTS rows, and vectors in SQLite

search_notes
  -> embed the query with Ollama
  -> score vector similarity
  -> score SQLite FTS5 keyword matches
  -> apply title/path/heading metadata boosts
  -> regroup chunk matches into file-level results

Default storage:

~/.obsidian-semantic-mcp/
  data/semantic.sqlite
  logs/
  cache/

The vault remains the source of truth. The SQLite database is a derived index and can be deleted/rebuilt.

Safety Model

The server reads your vault and never writes to it. Three layers decide what an agent can see.

1. Always denied (system / tooling). Never indexed, no override:

  • .obsidian/, .smart-env/, .claude/, .codex-*/
  • any hidden folder (name starts with .)
  • node_modules, cache, logs

2. Sensitive — denied by default, unlockable. Stays blocked even when a tool call passes include_sensitive: true, unless the server is started with OBSIDIAN_SEMANTIC_ALLOW_SENSITIVE=true. Defaults to 08_PersonalInfo/. Override the list with OBSIDIAN_SEMANTIC_SENSITIVE_PATHS (comma- or newline-separated folders):

OBSIDIAN_SEMANTIC_SENSITIVE_PATHS = "08_PersonalInfo, 09_Finance"

3. Your own excludes — always denied. Folders you never want indexed, searched, or read. No unlock flag:

OBSIDIAN_SEMANTIC_EXCLUDE = "03_Journal, Private, Clients/Acme"

Which one do you want?

  • "Don't index this at all"OBSIDIAN_SEMANTIC_EXCLUDE
  • "Keep it locked, but I can unlock it with a flag when I need to"OBSIDIAN_SEMANTIC_SENSITIVE_PATHS + OBSIDIAN_SEMANTIC_ALLOW_SENSITIVE

Additional guards:

  • All paths are resolved through realpath.
  • Path traversal and URL-encoded traversal are blocked.
  • Symlinks that escape the vault root are blocked.

Changing these lists only affects new indexing. Already-indexed notes keep their stored state until you reindex. After tightening EXCLUDE or SENSITIVE, run index_vault { "mode": "full" } so search_notes cannot surface stale hits. (read_note always enforces the live config.) You can confirm the active lists with index_status.

The local index stores snippets and embedding vectors. Treat it as a derived copy of your vault. See PRIVACY.md.

Indexing Strategy

The server does not watch your vault in real time.

After editing notes, run:

{ "mode": "incremental" }

This keeps the first public version predictable and avoids background watcher risks. You can opt into startup indexing with:

OBSIDIAN_SEMANTIC_STARTUP_INDEX = "true"

Development

npm test
npm run pack:check

Before publishing:

npm pack --dry-run

Confirm the package does not include data/, *.sqlite, or private vault files.

License

MIT

from github.com/DalecB/obsidian-semantic-mcp

Установить Obsidian Semantic Search в Claude Desktop, Claude Code, Cursor

Рекомендуется · одна команда, все IDE
unyly install obsidian-semantic-search

Ставит в Claude Desktop, Claude Code, Cursor и VS Code — сам разбирается с npx, uvx и сборкой из исходников.

Впервые? Поставь CLI: curl -fsSL https://unyly.org/install | sh

Или настроить вручную

Выполни в терминале:

claude mcp add obsidian-semantic-search -- npx -y @dalecb/obsidian-semantic-mcp

FAQ

Obsidian Semantic Search MCP бесплатный?

Да, Obsidian Semantic Search MCP бесплатный — установка в пару кликов через Unyly без оплаты.

Нужен ли API-ключ для Obsidian Semantic Search?

Нет, Obsidian Semantic Search работает без API-ключей и переменных окружения.

Obsidian Semantic Search — hosted или self-hosted?

Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.

Как установить Obsidian Semantic Search в Claude Desktop, Claude Code или Cursor?

Открой Obsidian Semantic Search на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.

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