Zettelkasten MCP Server

A Model Context Protocol (MCP) server that implements the Zettelkasten knowledge management methodology, allowing you to create, link, explore and synthesize atomic notes through Claude and other MCP-compatible clients.

What is Zettelkasten?

The Zettelkasten method is a knowledge management system developed by German sociologist Niklas Luhmann, who used it to produce over 70 books and hundreds of articles. It consists of three core principles:

1. Atomicity: Each note contains exactly one idea, making it a discrete unit of knowledge
2. Connectivity: Notes are linked together to create a network of knowledge, with meaningful relationships between ideas
3. Emergence: As the network grows, new patterns and insights emerge that weren't obvious when the individual notes were created

What makes the Zettelkasten approach powerful is how it enables exploration in multiple ways:

• Vertical exploration: dive deeper into specific topics by following connections within a subject area.
• Horizontal exploration: discover unexpected relationships between different fields by traversing links that cross domains.

This structure invites serendipitous discoveries as you follow trails of thought from note to note, all while keeping each piece of information easily accessible through its unique identifier. Luhmann called his system his "second brain" or "communication partner" - this digital implementation aims to provide similar benefits through modern technology.

Features

• Create atomic notes with unique timestamp-based IDs
• Link notes bidirectionally to build a knowledge graph
• Tag notes for categorical organization
• Search notes by content, tags, or links
• Use markdown format for human readability and editing
• Integrate with Claude through MCP for AI-assisted knowledge management
• Dual storage architecture (see below)
• Synchronous operation model for simplified architecture

Examples

• Knowledge creation: A small Zettelkasten knowledge network about the Zettelkasten method itself

Note Types

The Zettelkasten MCP server supports different types of notes:

Link Types

The Zettelkasten MCP server uses a comprehensive semantic linking system that creates meaningful connections between notes. Each link type represents a specific relationship, allowing for a rich, multi-dimensional knowledge graph.

Prompting

To ensure maximum effectiveness, we recommend using a system prompt ("project instructions"), project knowledge, and an appropriate chat prompt when asking the LLM to process information, or explore or synthesize your Zettelkasten notes. The docs directory in this repository contains the necessary files to get you started:

System prompts

Pick one:

• system-prompt.md
• system-prompt-with-protocol.md

Project knowledge

For end users:

• zettelkasten-methodology-technical.md
• link-types-in-zettelkasten-mcp-server.md
• (more info relevant to your project)

Chat Prompts

• chat-prompt-knowledge-creation.md
• chat-prompt-knowledge-creation-batch.md
• chat-prompt-knowledge-exploration.md
• chat-prompt-knowledge-synthesis.md

Project knowledge (dev)

For developers and contributors:

• Example - A simple MCP server.md
• MCP Python SDK-README.md
• llms-full.txt

NB: Optionally include the source code with a tool like repomix.

Storage Architecture

This system uses a dual storage approach:

1. Markdown Files: All notes are stored as human-readable Markdown files with YAML frontmatter for metadata. These files are the source of truth and can be:

   • Edited directly in any text editor
   • Placed under version control (Git, etc.)
   • Backed up using standard file backup procedures
   • Shared or transferred like any other text files

2. SQLite Database: Functions as an indexing layer that:

   • Facilitates efficient querying and search operations
   • Enables Claude to quickly traverse the knowledge graph
   • Maintains relationship information for faster link traversal
   • Is automatically rebuilt from Markdown files when needed

If you edit Markdown files directly outside the system, you'll need to run the zk_rebuild_index tool to update the database. The database itself can be deleted at any time - it will be regenerated from your Markdown files.

Installation

# Clone the repository
git clone https://github.com/entanglr/zettelkasten-mcp.git
cd zettelkasten-mcp

# Create a virtual environment with uv
uv venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

# Install dependencies
uv add "mcp[cli]"

# Install dev dependencies
uv sync --all-extras

Configuration

Create a .env file in the project root by copying the example:

cp .env.example .env

Then edit the file to configure your connection parameters.

Usage

Starting the Server

python -m zettelkasten_mcp.main

Or with explicit configuration:

python -m zettelkasten_mcp.main --notes-dir ./data/notes --database-path ./data/db/zettelkasten.db

Connecting to Claude Desktop

Add the following configuration to your Claude Desktop:

{
  "mcpServers": {
    "zettelkasten": {
      "command": "/absolute/path/to/zettelkasten-mcp/.venv/bin/python",
      "args": [
        "-m",
        "zettelkasten_mcp.main"
      ],
      "env": {
        "ZETTELKASTEN_NOTES_DIR": "/absolute/path/to/zettelkasten-mcp/data/notes",
        "ZETTELKASTEN_DATABASE_PATH": "/absolute/path/to/zettelkasten-mcp/data/db/zettelkasten.db",
        "ZETTELKASTEN_LOG_LEVEL": "INFO"
      }
    }
  }
}

Available MCP Tools

All tools have been prefixed with zk_ for better organization:

Project Structure

zettelkasten-mcp/
├── src/
│   └── zettelkasten_mcp/
│       ├── models/       # Data models
│       ├── storage/      # Storage layer
│       ├── services/     # Business logic
│       └── server/       # MCP server implementation
├── data/
│   ├── notes/            # Note storage (Markdown files)
│   └── db/               # Database for indexing
├── tests/                # Test suite
├── .env.example          # Environment variable template
└── README.md

Tests

Comprehensive test suite for Zettelkasten MCP covering all layers of the application from models to the MCP server implementation.

How to Run the Tests

From the project root directory, run:

Using pytest directly

python -m pytest -v tests/

Using UV

uv run pytest -v tests/