OpenClaw + Obsidian Integration: Turn Your Notes Into AI Memory

Last updated: April 26, 2026

AI assistants forget everything between sessions. Every conversation starts from zero. If you have complex projects, a rich personal context, and specific preferences, you're stuck re-explaining yourself — or getting generic responses.

What if your AI could remember everything? Your projects, your collaborators, your decisions, your preferences. What if every session built on the last, making your assistant genuinely more useful over time?

That's exactly what the OpenClaw + Obsidian integration delivers. By connecting OpenClaw to your Obsidian vault, you create a persistent AI memory system — a second brain that grows with you.

In this guide, you'll learn how to set up this powerful integration, configure it for your workflow, and unlock use cases that transform how you work with AI.

What Is OpenClaw Obsidian Integration?

OpenClaw is an AI assistant platform that runs on your machine, your servers, or in the cloud. It's designed for privacy, flexibility, and control — you choose where your data lives and which models power your assistant.

Obsidian is a powerful note-taking and knowledge management app built on local Markdown files. Your vault is your second brain: notes, ideas, projects, research, and connections.

The integration works through OpenClaw's MCP (Model Context Protocol) layer. MCP lets OpenClaw read and write to your Obsidian vault, giving your AI assistant:

Context loading: Read relevant notes at the start of each session
Memory persistence: Write insights, decisions, and updates back to your vault
Query capabilities: Search your notes, find connections, surface relevant context
Bi-directional sync: Your vault stays updated as you work with your AI

This means your AI assistant "knows" you — without you re-explaining yourself every time.

Why Use Obsidian as AI Memory?

The Problem: Amnesiac AI

Most AI assistants (ChatGPT, Claude web, Gemini) have no persistent memory. Each conversation is isolated. You can't reference past projects, ongoing decisions, or accumulated knowledge without copy-pasting.

Some platforms offer "memory" features, but they're limited:

Closed ecosystems: Your memory lives on their servers
No transparency: You can't see or edit what's stored
No portability: Can't export or migrate your memory
Privacy concerns: Sensitive context is uploaded to third parties

The Solution: OpenClaw + Obsidian

Using Obsidian as your AI memory solves all of these problems:

Feature	Cloud AI Memory	OpenClaw + Obsidian
Persistence	Limited, platform-dependent	Full, you own it
Transparency	Black box	All files visible & editable
Portability	Locked in	Standard Markdown, take it anywhere
Privacy	Uploaded to cloud	Local-first, you control access
Control	Platform decides	You configure everything

Your Obsidian vault becomes a living memory layer that your AI assistant reads and maintains.

How the Integration Works

Architecture Overview

The OpenClaw + Obsidian integration is built on MCP (Model Context Protocol). Here's the architecture:

┌─────────────────────────────────────────────────────────┐
│                    OpenClaw Agent                        │
│  (GLM-5, Claude, DeepSeek, or your chosen model)        │
└─────────────────────────────────────────────────────────┘
                           │
                           ▼
┌─────────────────────────────────────────────────────────┐
│                   MCP Server Layer                      │
│  - Obsidian MCP server (filesystem access)              │
│  - Context loading rules (what to read when)            │
│  - Write permissions (what AI can update)               │
└─────────────────────────────────────────────────────────┘
                           │
                           ▼
┌─────────────────────────────────────────────────────────┐
│                  Obsidian Vault                          │
│  - memory/ (AI-maintained wiki)                         │
│  - sources/ (your raw notes)                            │
│  - CLAUDE.md (identity & rules)                         │
│  - TASKS.md (active tasks)                              │
└─────────────────────────────────────────────────────────┘

Memory Layers

A well-structured Obsidian vault for AI memory typically has three layers:

Layer 1: Sources (sources/)
Raw inputs: articles, clips, podcast notes, book highlights. You add these; the AI reads but never modifies. Immutable reference material.

Layer 2: Wiki (memory/)
Structured knowledge: people, projects, decisions, insights, glossary. The AI writes and maintains this layer; you read and direct it.

Layer 3: Schema (CLAUDE.md, TASKS.md)
Identity, interaction rules, loading instructions. You and the AI co-evolve this over time.

Step-by-Step Setup Guide

Prerequisites

OpenClaw installed (version 1.12+)
Obsidian installed with an existing vault
Basic familiarity with YAML and Markdown

Step 1: Create the Memory Structure

In your Obsidian vault, create the following structure:

vault/
├── CLAUDE.md           # Identity and rules
├── TASKS.md            # Active tasks
├── sources/            # Your raw notes
│   ├── articles/
│   ├── notes/
│   └── clips/
└── memory/             # AI-maintained wiki
    ├── schema.md
    ├── index.md
    ├── log.md
    ├── glossary.md
    ├── working-context.md
    └── projects/

Step 2: Create CLAUDE.md

This file defines how OpenClaw should behave with your vault:

# CLAUDE.md - AI Identity

## Who I Am
I am your AI assistant, integrated with this Obsidian vault. I have persistent memory of your projects, decisions, and context.

## Memory Loading Rules
At the start of each session:
1. Read `memory/working-context.md` for current focus
2. Read `TASKS.md` for active tasks
3. Read relevant project files based on context

## Write Permissions
I can update:
- `memory/` directory (wiki pages)
- `TASKS.md` (task status)
- `memory/log.md` (operation log)

I cannot modify:
- `sources/` directory (your raw notes)

## Interaction Style
- Be concise but thorough
- Reference relevant notes when making suggestions
- Update memory after significant decisions

Step 3: Configure MCP Server

In your OpenClaw configuration (typically ~/.openclaw/config.yaml), add the Obsidian MCP server:

mcp:
  servers:
    obsidian:
      command: "npx"
      args:
        - "-y"
        - "@anthropic/mcp-server-filesystem"
        - "/path/to/your/obsidian/vault"
      env: {}

Alternatively, use the OpenClaw CLI:

openclaw mcp add obsidian --command "npx -y @anthropic/mcp-server-filesystem /path/to/vault"

Step 4: Test the Connection

Start a session with OpenClaw and verify the connection:

openclaw chat

You: What's in my working context file?
AI: Let me check your memory/working-context.md...
[Reads and summarizes the file]

If OpenClaw can read your files, the integration is working.

Step 5: Configure Context Loading

Create a triggers.md file in your memory directory to define automatic loading rules:

# Memory Triggers

## Keyword → File Loading
- "project" → load `memory/projects/`
- "decision" → load `memory/decisions.md`
- "deadline" → load `TASKS.md`
- "person" → load `memory/people/`

## Proactive Writing Rules
- After each session, update `memory/working-context.md`
- When a decision is made, log to `memory/log.md`
- When a new project is mentioned, create `memory/projects/[name].md`

Use Cases

1. Research Projects

You're researching "AI memory systems." You save articles, notes, and quotes to sources/research/ai-memory/. When you ask OpenClaw for help, it:

Loads relevant research notes
Suggests connections between papers
Summarizes findings
Writes insights back to memory/research/ai-memory.md

Each session builds on the last without re-uploading context.

2. Meeting Preparation

Before a meeting, OpenClaw loads:

Previous meeting notes for this project
Action items from TASKS.md
Context about attendees from memory/people/

After the meeting, it updates:

memory/log.md with decisions made
TASKS.md with new action items
memory/projects/[project].md with progress

3. Writing & Content Creation

You're writing a blog series. OpenClaw:

Reads your style guide from memory/style-guide.md
References previous posts in the series
Maintains consistency across installments
Tracks word counts and deadlines

4. Learning & Skill Development

You're learning a new programming language. OpenClaw:

Tracks your progress in memory/learning/[language].md
Notes concepts you've mastered
Suggests next topics based on gaps
Remembers your learning style preferences

5. Personal Productivity

You're managing multiple projects. OpenClaw:

Surfaces context based on current focus
Reminds you of upcoming deadlines
Tracks recurring tasks in TASKS.md
Maintains a decision log for future reference

Advanced Configuration

Custom MCP Servers

For more control, you can build a custom Obsidian MCP server:

# obsidian-mcp-server.py
import json
import sys
from pathlib import Path

VAULT_PATH = "/path/to/your/vault"

def handle_request(request):
    if request["method"] == "read_file":
        path = Path(VAULT_PATH) / request["params"]["path"]
        return {"content": path.read_text()}
    elif request["method"] == "write_file":
        path = Path(VAULT_PATH) / request["params"]["path"]
        path.write_text(request["params"]["content"])
        return {"success": True}
    # Add more methods as needed

for line in sys.stdin:
    request = json.loads(line)
    response = handle_request(request)
    print(json.dumps(response), flush=True)

openclaw mcp add obsidian-custom --command "python /path/to/obsidian-mcp-server.py"

Security Best Practices

Limit write permissions: Only allow AI to write to specific directories
Use git for version control: Track changes to your vault
Audit logs: Review memory/log.md regularly
Backup regularly: Use Obsidian's backup plugin or git

Performance Optimization

Selective loading: Only load relevant files, not entire vault
Index files: Maintain memory/index.md for quick lookups
Lazy loading: Load detailed context only when needed
Caching: OpenClaw caches context within a session

How This Compares to Alternatives

vs. Cloud-Based Memory (ChatGPT Memory, Claude Projects)

Aspect	Cloud Memory	OpenClaw + Obsidian
Data ownership	Stored on provider servers	Local files, you own it
Privacy	Uploaded to cloud	Stays on your machine
Transparency	Black box	All files editable
Portability	Locked to platform	Standard Markdown
Cost	Subscription required	Free after setup