obsidian-mcp-plugin

aaronsb/obsidian-mcp-plugin

3.6

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The Obsidian MCP Plugin is a high-performance server that integrates Model Context Protocol capabilities directly into Obsidian, providing AI tools with direct vault access through HTTP transport.

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Obsidian MCP Plugin

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Give AI semantic agency over your knowledge graph

This plugin connects your Obsidian vault to AI assistants through MCP (Model Context Protocol), giving them the ability to understand and navigate your notes as a connected knowledge graph, not just isolated files. Through semantic hints and graph traversal, AI gains the agency to explore concepts, follow connections, and synthesize information across your entire vault.

MCP (Model Context Protocol) is the open standard that lets AI assistants interact with external tools and data sources. This plugin works with any MCP-compatible client including:

  • Claude Desktop (Anthropic)
  • Claude Code/Continue.dev (VS Code)
  • Any platform that supports local MCP servers

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πŸ“¦ Release Downloads

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Why Semantic MCP?

Traditional file access gives AI a narrow view - one document at a time. This plugin transforms that into semantic agency:

  • Graph Navigation: AI follows links between notes, understanding relationships and context
  • Concept Discovery: Semantic search finds related ideas across your vault
  • Contextual Awareness: AI understands where information lives in your knowledge structure
  • Intelligent Synthesis: Combine fragments from multiple notes to answer complex questions

Quick Start

Prerequisites: You need an MCP-compatible AI client like Claude Desktop, Claude Code, or Continue.dev.

1. Install the Plugin

Via Obsidian Community Plugins (coming soon)

  • Open Settings β†’ Community plugins
  • Search for "Semantic MCP"
  • Install and enable

Via BRAT (for beta testing)

  • Install BRAT
  • Add beta plugin: aaronsb/obsidian-mcp-plugin

2. Configure Your AI Client

For Claude Desktop / Claude Code

{
  "mcpServers": {
    "obsidian-vault": {
      "command": "npx",
      "args": ["mcp-remote", "http://localhost:3001/mcp"]
    }
  }
}

With Authentication (if enabled in plugin settings)

{
  "mcpServers": {
    "obsidian-vault": {
      "command": "npx",
      "args": [
        "mcp-remote",
        "https://localhost:3443/mcp",
        "--header",
        "Authorization:${AUTH}"
      ],
      "env": {
        "NODE_TLS_REJECT_UNAUTHORIZED": "0",
        "AUTH": "Bearer YOUR_API_KEY"
      }
    }
  }
}

3. Start Using

Once connected, simply chat with your AI assistant about your notes! For example:

  • "What are my recent thoughts on project X?"
  • "Find connections between my psychology and philosophy notes"
  • "Summarize my meeting notes from this week"
  • "Create a new note linking my ideas about Y"

Your AI assistant now has these capabilities:

  • Navigate your vault's link structure
  • Search across all notes semantically
  • Read, edit, and create notes
  • Analyze your knowledge graph
  • Work with Dataview queries (if installed)
  • Manage Obsidian Bases (database views)

Core Tools

The plugin provides 8 semantic tool groups that give AI comprehensive vault access:

ToolPurposeKey Actions
πŸ“ vaultFile operationslist, read, create, search, move, split, combine
✏️ editContent modificationwindow editing, append, patch sections
πŸ‘οΈ viewContent displayview files, windows, active note
πŸ•ΈοΈ graphLink navigationtraverse, find paths, analyze connections
πŸ’‘ workflowContextual hintssuggest next actions based on state
πŸ“Š dataviewQuery notesExecute DQL queries (if installed)
πŸ—ƒοΈ basesDatabase viewsQuery and export Bases (if available)
ℹ️ systemVault infoServer status, commands, web fetch

Documentation

Detailed documentation for each tool and feature:

  • - File management and search
  • - Content modification strategies
  • - Link traversal and analysis
  • - Query language support
  • - API keys and permissions
  • - Server settings and options
  • - Common issues and solutions

The Semantic Advantage

This plugin doesn't just give AI access to files - it provides semantic understanding:

Example: Research Assistant

User: "Summarize my research on machine learning optimization"

AI uses semantic tools to:
1. Search for notes with ML optimization concepts
2. Traverse graph to find related papers and techniques  
3. Follow backlinks to discover applications
4. Synthesize findings from multiple connected notes

Example: Knowledge Explorer

User: "What connections exist between my notes on philosophy and cognitive science?"

AI uses graph tools to:
1. Find notes tagged with both topics
2. Analyze shared concepts via graph traversal
3. Identify bridge notes that connect domains
4. Map the conceptual overlap

Features

Semantic Search

  • Advanced query operators: tag:, path:, content:
  • Regular expressions and phrase matching
  • Relevance ranking and snippet extraction

Graph Intelligence

  • Multi-hop traversal with depth control
  • Backlink and forward-link analysis
  • Path finding between concepts
  • Tag-based navigation

Content Operations

  • Fuzzy text matching for edits
  • Structure-aware modifications (headings, blocks)
  • Batch operations (split, combine, move)
  • Template support

Integration

  • Dataview query execution
  • Bases database operations
  • Web content fetching
  • Read-only mode for safety

Plugin Settings

Access settings via: Settings β†’ Community plugins β†’ Semantic MCP

Key configuration options:

  • Server Ports: HTTP (3001) and HTTPS (3443)
  • Authentication: API key protection
  • Security: Path validation and permissions
  • Performance: Connection pooling and caching

Support

License

MIT