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Semlink

by Ouzhongyuan
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Description

This plugin has not been manually reviewed by Obsidian staff. Semantic search for Obsidian Vault via MCP

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Latest Version

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Changelog

See all version on GitHub

README file from

Github

Semlink

中文

An Obsidian plugin that vectorizes your Vault notes and exposes semantic search via MCP (Model Context Protocol).

Let Claude Desktop, Claude Code, Cursor and other AI tools directly search and read your Obsidian notes.

Features

  • Semantic Search: Query your Vault notes in natural language, return the most relevant results based on vector similarity
  • Real-time Indexing: Automatically detect file changes and update the vector index
  • MCP Server: Expose search capabilities via HTTP protocol for AI clients

MCP Tools

Tool Description
search_notes Semantic search notes using natural language queries, returns the most relevant note chunks
get_note Get the full content of a note
get_similar_notes Find notes semantically similar to a specified note
get_section Get the content under a specific heading in a note
list_indexed List all indexed notes
index_status Get current indexing status and progress
reindex Trigger re-indexing (single file or full)

How It Works

Obsidian Vault Notes
        │
        ▼
   Text Chunking
        │
        ▼
  SiliconFlow API (BGE-M3)  ──→  Vector Embedding
        │
        ▼
  Local Storage (SQLite + Binary)
        │
        ▼
  MCP HTTP Server (:3001)
        │
        ▼
  Claude / Cursor / Other AI Clients

Installation

Option 1: Build from Source (Developers)
# Clone the repo
git clone https://github.com/ouou365/Semlink.git
cd semlink

# Install dependencies
npm install

# Build
npm run build

# Copy the entire directory to your Obsidian Vault plugins folder
# e.g. MyVault/.obsidian/plugins/semlink/
Option 2: Direct Download

Download main.js, manifest.json, styles.css, sql-wasm.wasm from the Release page and place them in:

YourVault/.obsidian/plugins/semlink/
Enable the Plugin
  1. Open Obsidian → Settings → Community plugins
  2. Find Semlink and enable it

Configuration

After enabling the plugin, go to Settings → Semlink:

Setting Description Default
SiliconFlow API Key API key from siliconflow.cn (Required)
Embedding Model Model used for vectorization BAAI/bge-m3
MCP Port HTTP server listening port 3001
MCP Access Key Authentication key for MCP clients (leave empty to disable) Empty
Chunk Size Maximum characters per text chunk 800
Chunk Overlap Overlap characters between adjacent chunks 100
Batch Size Number of texts per API call 64
Request Delay Delay between API requests (ms) 200
Exclude Paths Paths excluded from indexing (one per line) templates/ etc.
Auto Index Automatically update on file changes On
Getting an API Key
  1. Register at siliconflow.cn
  2. Create an API Key in the console
  3. Enter the key in plugin settings

Connect AI Clients

After configuration, client configs are auto-generated at the bottom of the plugin settings page.

Claude Desktop / Cursor

Add the following JSON to your MCP configuration file:

{
  "mcpServers": {
    "semlink": {
      "type": "http",
      "url": "http://127.0.0.1:3001/mcp"
    }
  }
}

With MCP access key:

{
  "mcpServers": {
    "semlink": {
      "type": "http",
      "url": "http://127.0.0.1:3001/mcp",
      "headers": {
        "Authorization": "Bearer your-key"
      }
    }
  }
}
Claude Code

Run in terminal:

# Without key
claude mcp add --transport http semlink http://127.0.0.1:3001/mcp

# With key
claude mcp add --transport http semlink http://127.0.0.1:3001/mcp --header "Authorization: Bearer your-key"

Usage

First Indexing
  1. Configure your API Key
  2. Open command palette (Ctrl/Cmd + P), search for "Semlink: Start Index"
  3. Click Semlink in the status bar to view indexing progress
Daily Use
  • The plugin automatically watches for file changes and incrementally updates the index
  • Ask questions in your AI client to search your notes
Commands
Command Description
Semlink: Full Reindex Re-scan all files
Semlink: Start Index Start indexing
Semlink: Pause Index Pause current indexing
Semlink: Start/Stop MCP Service Toggle MCP server
Semlink: View Index Progress Open progress panel

Data Storage

All data is stored locally only:

File Description
data/vault.db SQLite database for chunk metadata
data/vectors.bin Vector index binary file

These files are located in the plugin directory and are never uploaded to any server.

Embedding Models

Model Feature Max Tokens
BAAI/bge-m3 Recommended, multilingual 8192
Pro/BAAI/bge-m3 Enhanced version 8192
BAAI/bge-large-zh-v1.5 Chinese optimized 512
BAAI/bge-large-en-v1.5 English optimized 512

Tech Stack

  • Embedding: SiliconFlow API (BGE-M3, 1024-dim)
  • Storage: sql.js (SQLite WASM) + binary vector file
  • Search: Brute-force cosine similarity
  • Protocol: MCP over HTTP (JSON-RPC 2.0)

Development

# Dev mode (watch and auto-rebuild)
npm run dev

# Production build
npm run build

Notes

  • Full indexing consumes SiliconFlow API credits; watch your usage for large Vaults
  • Vector search runs in local memory; 100K+ notes may use significant memory
  • MCP server listens on 127.0.0.1 by default, accessible only from localhost

License

MIT

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