Obsidian Semantic MCP Server

> 🎉 Exciting News! We've taken everything we learned from this project and created something even better! Check out the new **Obsidian MCP Plugin** - a native Obsidian plugin that runs directly inside your vault with improved performance, simplified setup, and enhanced features. We encourage you to try it out!

A semantic, AI-optimized MCP server for Obsidian that consolidates 20 tools into 5 intelligent operations with contextual workflow hints.

🚀 Try Our New Native Plugin!

This MCP server taught us valuable lessons about AI integration with Obsidian. We've applied these insights to create the **Obsidian MCP Plugin**, which offers:

• Native Integration: Runs directly inside Obsidian (no external dependencies!)
• Better Performance: Direct vault access without REST API overhead
• Easier Setup: Install like any Obsidian plugin - no API keys or external servers
• Enhanced Features: Full access to Obsidian's internal APIs and search capabilities
• Improved Reliability: No more connection issues or timeouts

👉 **Get the Obsidian MCP Plugin**

Prerequisites

• Obsidian installed on your computer
• Local REST API plugin installed in your Obsidian vault
• Claude Desktop app

Installation

npm install -g obsidian-semantic-mcp

Or use directly with npx (recommended):

npx obsidian-semantic-mcp

View on npm: https://www.npmjs.com/package/obsidian-semantic-mcp

Quick Start

1. Install the Obsidian Plugin:

2. Configure Claude Desktop:

The npx command is automatically used in the Claude Desktop configuration. Add this to your Claude Desktop config (usually found at `~/Library/Application Support/Claude/claude_desktop_config.json` on macOS):

{
     "mcpServers": {
       "obsidian": {
         "command": "npx",
         "args": ["-y", "obsidian-semantic-mcp"],
         "env": {
           "OBSIDIAN_API_KEY": "your-api-key-here",
           "OBSIDIAN_API_URL": "https://127.0.0.1:27124",
           "OBSIDIAN_VAULT_NAME": "your-vault-name"
         }
       }
     }
   }

Features

This server consolidates traditional MCP tools into an AI-optimized semantic interface that makes it easier for AI agents to understand and use Obsidian operations effectively.

Key Benefits

• Simplified Interface: 5 semantic operations instead of 21+ individual tools
• Contextual Workflows: Intelligent hints guide AI agents to the next logical action
• State Tracking: Token-based system prevents invalid operations
• Error Recovery: Smart recovery hints when operations fail
• Fuzzy Matching: Resilient text editing that handles minor variations
• Fragment Retrieval: Automatically returns relevant sections from large files to conserve tokens

Why Semantic Operations?

Traditional MCP servers expose many granular tools (20+), which can overwhelm AI agents and lead to inefficient tool selection. Our semantic approach:

• Consolidates 20 tools into 5 semantic operations based on intent
• Provides contextual workflow hints to guide next actions
• Tracks state with tokens (inspired by Petri nets) to prevent nonsensical suggestions
• Offers recovery hints when operations fail

The 5 Semantic Operations

1. `vault` - File and folder operations

2. `edit` - Smart content editing

3. `view` - Content viewing and navigation

4. `workflow` - Get guided suggestions

5. `system` - System operations

Example Usage

Instead of choosing between `get_vault_file`, `get_active_file`, `read_file_content`, etc., you simply use:

{
  "operation": "vault",
  "action": "read",
  "params": {
    "path": "daily-notes/2024-01-15.md"
  }
}

The response includes intelligent workflow hints:

{
  "result": { /* file content */ },
  "workflow": {
    "message": "Read file: daily-notes/2024-01-15.md",
    "suggested_next": [
      {
        "description": "Edit this file",
        "command": "edit(action='window', path='daily-notes/2024-01-15.md', ...)",
        "reason": "Make changes to content"
      },
      {
        "description": "Follow linked notes",
        "command": "vault(action='read', path='{linked_file}')",
        "reason": "Explore connected knowledge"
      }
    ]
  }
}

State-Aware Suggestions

The system tracks context tokens to provide relevant suggestions:

• After reading a file with `[[links]]`, it suggests following them
• After a failed edit, it offers buffer recovery options
• After searching, it suggests refining or reading results

Advanced Features

Content Buffering

The `window` edit action automatically buffers your new content before attempting the edit. If the edit fails or you want to refine it, you can retrieve from buffer:

{
  "operation": "edit",
  "action": "from_buffer",
  "params": {
    "path": "notes/meeting.md"
  }
}

Fuzzy Window Editing

The semantic editor uses fuzzy matching to find and replace content:

{
  "operation": "edit",
  "action": "window",
  "params": {
    "path": "daily/2024-01-15.md",
    "oldText": "meting notes",  // typo will be fuzzy matched
    "newText": "meeting notes",
    "fuzzyThreshold": 0.8
  }
}

Smart PATCH Operations

Target specific document structures:

{
  "operation": "edit",
  "action": "patch",
  "params": {
    "path": "projects/todo.md",
    "operation": "append",
    "targetType": "heading",
    "target": "## In Progress",
    "content": "- [ ] New task"
  }
}

Fragment Retrieval for Large Documents

The system automatically uses intelligent fragment retrieval when reading files, significantly reducing token consumption while maintaining relevance:

{
  "operation": "vault",
  "action": "read",
  "params": {
    "path": "large-document.md"
  }
}

Returns relevant fragments instead of the entire file:

{
  "result": {
    "content": [
      {
        "id": "file:large-document.md:frag0",
        "content": "Most relevant section...",
        "score": 0.95,
        "lineStart": 145,
        "lineEnd": 167
      }
    ],
    "fragmentMetadata": {
      "totalFragments": 5,
      "strategy": "adaptive",
      "originalContentLength": 135662
    }
  }
}

Fragment Search Strategies:

• adaptive - TF-IDF keyword matching (default for short queries)
• proximity - Finds fragments where query terms appear close together
• semantic - Chunks documents into meaningful sections

You can explicitly search for fragments across your vault:

{
  "operation": "vault",
  "action": "fragments",
  "params": {
    "query": "project roadmap timeline",
    "maxFragments": 10,
    "strategy": "proximity"
  }
}

To retrieve the full file (when needed), use:

{
  "operation": "vault",
  "action": "read",
  "params": {
    "path": "document.md",
    "returnFullFile": true
  }
}

Workflow Examples

Daily Note Workflow

1. Create today's note → 2. Add template → 3. Link yesterday's note

Research Workflow

1. Search topic → 2. Read results → 3. Create synthesis note → 4. Link sources

Refactoring Workflow

1. Find all mentions → 2. Update links → 3. Rename/merge notes

Configuration

The semantic workflow hints are defined in `src/config/workflows.json` and can be customized for your workflow preferences.

Fragment Retrieval Configuration

The fragment retrieval system automatically activates when reading files to conserve tokens. You can control this behavior:

• Default behavior: Returns up to 5 relevant fragments when reading files
• Full file access: Use `returnFullFile: true` parameter to get complete content
• Strategy selection: The system auto-selects based on query length, or you can specify:
  • `adaptive` for keyword matching (1-2 word queries)
  • `proximity` for finding related terms together (3-5 word queries)
  • `semantic` for conceptual chunking (longer queries)

Error Recovery

When operations fail, the semantic interface provides intelligent recovery hints:

{
  "error": {
    "code": "FILE_NOT_FOUND",
    "message": "File not found: daily/2024-01-15.md",
    "recovery_hints": [
      {
        "description": "Create this file",
        "command": "vault(action='create', path='daily/2024-01-15.md')"
      },
      {
        "description": "Search for similar files",
        "command": "vault(action='search', query='2024-01-15')"
      }
    ]
  }
}

Environment Variables

The server automatically loads environment variables from a `.env` file if present. Variables can be set in order of precedence:

1. Existing environment variables (highest priority)

2. `.env` file in current working directory

3. `.env` file in the server directory

Required variables:

• `OBSIDIAN_API_KEY` - Your API key from the Local REST API plugin

Optional variables:

• `OBSIDIAN_API_URL` - API URL (default: https://localhost:27124)
  • Supports both HTTP (port 27123) and HTTPS (port 27124)
  • HTTPS uses self-signed certificates which are automatically accepted
• `OBSIDIAN_VAULT_NAME` - Vault name for context

Example `.env` file:

OBSIDIAN_API_KEY=your-api-key-here
OBSIDIAN_API_URL=http://127.0.0.1:27123
OBSIDIAN_VAULT_NAME=MyVault

PATCH Operations

The PATCH operations (`patch_active_file` and `patch_vault_file`) allow sophisticated content manipulation:

• Target Types:
  • `heading`: Target content under specific headings using paths like "Heading 1::Subheading"
  • `block`: Target specific block references
  • `frontmatter`: Target frontmatter fields

• Operations:
  • `append`: Add content after the target
  • `prepend`: Add content before the target
  • `replace`: Replace the target content

Example: Append content under a specific heading:

{
  "operation": "append",
  "targetType": "heading",
  "target": "Daily Notes::Today",
  "content": "- New task added"
}

Development

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

# Development mode
npm run dev

# Testing
npm test              # Run all tests
npm run test:coverage # With coverage report

# Build
npm run build         # Build the server
npm run build:full    # Test + Build

# Start
npm start             # Start the server

Architecture

The semantic system consists of:

• Semantic Router (`src/semantic/router.ts`) - Routes operations to handlers
• State Tokens (`src/semantic/state-tokens.ts`) - Tracks context state
• Workflow Config (`src/config/workflows.json`) - Defines hints and suggestions
• Core Utilities (`src/utils/`) - Shared functionality like file reading and fuzzy matching

Testing

The project includes comprehensive Jest tests for the semantic system:

npm test                    # Run all tests
npm test semantic-router    # Test routing logic
npm test semantic-tools     # Test integration

Known Issues

• Search functionality: The search operation may occasionally timeout on large vaults due to API limitations in the Obsidian Local REST API plugin.

Contributing

Contributions are welcome! Areas of interest:

• Additional workflow patterns in `workflows.json`
• New semantic operations
• Enhanced state tracking
• Integration with Obsidian plugins

License

MIT