duckbrain 0.6.0

DuckDB-backed MCP memory server for Obsidian vaults — structured search, read, and write access for AI coding agents.

DuckBrain

DuckDB-backed MCP memory server for Obsidian vaults. Gives AI coding agents read/write access to your personal wiki — structured pages, full-text search, automatic indexing.

Installation

Install DuckBrain:

pip install duckbrain

... or with the dependency manager of your choice (uv, poetry, ...)

Then pick your agent:

• OpenCode — MCP server + session plugin (recommended)
• Claude Code — MCP server + CLAUDE.md + SessionStart hook
• Cursor — MCP server + rules + hooks
• Hermes — MCP server + AGENTS.md
• Other Agents (e.g. Codex, Gemini) will follow after testing

---

OpenCode

Best experience (as I use OpenCode myself) — session plugin gives the AI automatic vault awareness.

Add to opencode.json:

{
  "mcp": {
    "duckbrain": {
      "command": "duckbrain",
      "env": { "VAULT_PATH": "/path/to/your/vault" }
    }
  }
}

Download the session plugin (you need bun for the install):

mkdir -p ~/.config/opencode/plugins/
cd ~/.config/opencode/plugins

for f in vault-context.ts vault-context-helpers.ts package.json; do
  curl -O "https://raw.githubusercontent.com/timhiebenthal/duckbrain/main/opencode/plugins/$f"
done

bun install

Restart OpenCode. The plugin gives your AI automatic vault awareness and a few useful defaults:

• Vault-aware context — your AI sees your vault's topics, recent notes, and today's daily entry automatically. No need to ask "what's in my vault" or paste paths.
• Daily note journaling — the AI captures session progress, decisions, and discoveries into your daily note as you work, so you don't lose context between sessions.
• Real local-time timestamps — entries are timestamped with your actual local time, not whatever the AI guesses.
• End-of-session save — when you finish a session, the AI is prompted to journal anything new before the conversation closes. (Window close is still a loss — use /journal for guaranteed save.)

---

Claude Code

Prerequisite: uv or uvx on your PATH — the plugin runs the MCP server via uvx duckbrain (no manual pip install needed; uvx fetches and caches it automatically)

Install via plugin marketplace

claude plugin marketplace add /path/to/duckbrain/claude/
claude plugin install duckbrain@duckbrain-local
# Claude Code prompts for your vault path, or pass it non-interactively:
# claude plugin install duckbrain@duckbrain-local --config vault_path=/path/to/vault

Claude Code prompts for your vault path at enable time — no manual VAULT_PATH env var needed.

What you get

Enable plugin → prompted for vault path once
     ↓
Session start → SessionStart injects LEARNINGS guard + tags + daily notes
     ↓
During session → guard prompts Claude to journal after non-trivial work
     ↓
Every ~15 min → UserPromptSubmit re-surfaces the concise journal nudge (throttled)
     ↓
Context full → PreCompact injects snapshot + journal nudge
     ↓
Session end → type /journal → Claude writes summary to daily note
     ↓
SessionEnd hook → appends "Session end — HH:MM" timestamp

The plugin bundles four hooks (SessionStart, UserPromptSubmit, PreCompact, SessionEnd), the duckbrain MCP server config, and a /journal slash command. No manual settings.json editing.

Manual wiring (advanced)

If you prefer wiring hooks yourself without the plugin, the standalone scripts in scripts/claude-vault-*.sh still work — see the comments in each file for the required settings.json entries.

---

Cursor

Full vault awareness via .cursorrules (injected into every system prompt), MCP server, /journal slash command, and a SessionEnd hook. See cursor/README.md for complete setup.

Quick setup:

# 1. Copy .cursorrules to your project root
cp cursor/.cursorrules /path/to/your/project/.cursorrules

# 2. Copy MCP config to your project
mkdir -p /path/to/your/project/.cursor
cp cursor/.cursor/mcp.json /path/to/your/project/.cursor/mcp.json
# Edit mcp.json: replace /path/to/duckbrain with your actual clone path

# 3. Copy /journal command
mkdir -p /path/to/your/project/.cursor/commands
cp cursor/commands/journal.md /path/to/your/project/.cursor/commands/journal.md

# 4. Install SessionEnd hook
mkdir -p ~/.cursor/hooks/
cp cursor/hooks/vault-journal.sh ~/.cursor/hooks/vault-journal.sh
chmod +x ~/.cursor/hooks/vault-journal.sh

Wire the hook in ~/.cursor/hooks.json:

{
  "version": 1,
  "hooks": {
    "sessionEnd": [
      { "command": "/home/youruser/.cursor/hooks/vault-journal.sh" }
    ]
  }
}

Session flow: .cursorrules is injected every turn → AI calls vault_context() at session start to load daily notes and search results → guard prompts AI to journal after non-trivial work → /journal writes summary → SessionEnd hook appends timestamp.

Known gaps: no unsolicited journal nudge (no session.idle hook in Cursor), no automatic SessionStart injection (the hook is confirmed broken by Cursor devs — .cursorrules fills the gap reliably).

---

Hermes Agent

Has been tested and validated.

Add to mcp.json:

{
  "mcpServers": {
    "duckbrain": {
      "command": "uv",
      "args": ["run", "duckbrain"],
      "env": { "VAULT_PATH": "/path/to/your/vault" }
    }
  }
}

Add to AGENTS.md:

# DuckBrain vault
Call vault_info() at session start to discover vault topics.
Use vault_search() when the query matches vault content.
After non-trivial work, save learnings with vault_write().

Restart Hermes.

---

Tools

Tool	What it does
vault_search	Full-text search over vault pages
vault_read	Read a page by title or filepath
vault_write	Create a page or append to today's daily note
vault_context	Load daily notes + keyword search in one call
vault_info	Vault stats: page counts, tags, last modified

---

Vault Schema

your-vault/
├── wiki/
│   ├── entities/       # people, orgs, tools
│   ├── concepts/       # ideas, frameworks
│   ├── sources/        # summaries of ingested content
│   ├── synthesis/      # cross-cutting analysis
│   ├── index.md        # page catalog (auto-updated)
│   ├── log.md          # write history (auto-updated)
│   └── tags.md         # topic index (auto-updated)
├── daily/              # daily notes (YYYY-MM-DD.md)
└── .env                # VAULT_PATH (optional)

Pages use YAML frontmatter:

---
title: Claude Mem
item-type: entity
tags: [ai, memory, mcp]
created: 2026-05-28
updated: 2026-05-28
---

---

Nerdy Details

Implementation internals — not needed for installation.

Architecture

┌──────────────────────────────────────────────────────────────┐
│                      AI Agent                                │
│  ┌──────────────────────────┐  ┌──────────────────────────┐  │
│  │ MCP Client (stdio)       │  │ Hooks / Plugins          │  │
│  │  vault_search,           │  │ (SessionStart, system    │  │
│  │  vault_read, vault_write │  │  transform — inject      │  │
│  │  vault_context, vault_info│  │  vault context into      │  │
│  │                          │  │  system prompt)          │  │
│  └──────────┬───────────────┘  └──────────┬───────────────┘  │
└─────────────│──────────────────────────────│──────────────────┘
              │ MCP stdio                    │ reads directly
              ▼                              ▼ from vault
┌──────────────────────────────┐  ┌──────────────────────────────┐
│  DuckBrain MCP Server        │  │ Side channel:                │
│  vault_info   ──► DuckDB FTS │  │  wiki/tags.md                │
│  vault_search ──► DuckDB FTS │  │  daily/YYYY-MM-DD.md         │
│  vault_read   ──► Filesystem │  │  wiki/log.md                 │
│  vault_write  ──► Filesystem │  │                              │
└──────────────┬───────────────┘  └──────────────────────────────┘
               │ reads/writes
               ▼
┌──────────────────────────────────────────────────────────────────────┐
│                     Your Obsidian Vault                              │
│  wiki/entities/  wiki/concepts/  wiki/sources/  wiki/synthesis/      │
│  daily/          wiki/index.md   wiki/log.md    wiki/tags.md         │
└──────────────────────────────────────────────────────────────────────┘

• Reads vault files directly — no index to sync, no watchers, no duplicate storage
• Searches via DuckDB FTS (BM25 ranking), rebuilt fresh from disk on every query
• Writes new pages with YAML frontmatter, auto-updating index, log, and tags

Inspirations

This project stands on the shoulders of several ideas and tools:

• Andrej Karpathy's LLM wiki pattern — the idea that a personal markdown wiki, co-maintained by humans and AI agents, compounds into a persistent knowledge base. The vault schema (entities, concepts, sources, synthesis, daily log) is directly inspired by this.
• DuckDB — the embedded analytical database that makes full-text search over flat files viable without a server, index sync, or persistent storage. The decision to use in-memory FTS instead of a vector database was a deliberate trade-off for simplicity.
• Obsidian — the local-first, markdown-native note-taking tool that treats your files as the truth. DuckBrain exists because Obsidian vaults deserve tooling that respects the filesystem.
• MemSearch and Open Brain (OB1) — early experiments in cross-tool agent memory that demonstrated the need for structured vault write-back while choosing different architectures. Their strengths and gaps directly informed DuckBrain's design.
• Agent Memory Systems (6-level taxonomy) — Simon Scrapes' comprehensive comparison of Claude Code memory approaches provided the framework for understanding where DuckBrain fits in the ecosystem (Level 6: cross-tool MCP with dedicated server).
• trellis-datamodel — the same author's data modeling tool whose CI/CD patterns (trusted PyPI publishing, version-diff release detection, Keep a Changelog) were borrowed for this project's repository readiness.
• mondayDB 3 — Solving HTAP for a Trillion-Table System — monday.com's engineering blog on their DuckDB-powered CQRS read serving layer at production scale. Proved that DuckDB in-process with per-tenant file isolation is a viable architecture — the same pattern DuckBrain applies at personal-wiki scale.

The core decision — build, don't integrate — came from a structured comparison of 7 existing tools. All failed on one requirement: vault schema-aware write-back. Rather than fork or extend, DuckBrain started from first principles: what's the simplest thing that gives agents structured read/write access to an Obsidian vault? The answer was DuckDB + MCP + ~500 lines of Python.

---

Building from Source

git clone https://github.com/timhiebenthal/duckbrain.git
cd duckbrain
uv sync
uv run duckbrain  # will hang waiting on stdio — that's correct