Obsidian-in-a-Vat
AI-native knowledge vault MCP server: capture thoughts, auto-promote to structured notes, and build a knowledge graph with Louvain clustering, all from Claude Desktop.
vault-mcp
English
Personal knowledge vault MCP server for Claude Desktop. Capture thoughts, search notes, and read files from a local markdown-based knowledge vault.
Quick Start (Docker — Recommended)
Step 1. Make sure Docker Desktop is running.
Step 2. Add to your Claude Desktop config (~/Library/Application Support/Claude/claude_desktop_config.json):
{
"mcpServers": {
"vault": {
"command": "docker",
"args": [
"run", "-i", "--rm",
"-v", "/Users/yourname/my-vault:/vault",
"ghcr.io/oliverxuzy-ai/obsidian-in-a-vat:latest"
]
}
}
}
Replace /Users/yourname/my-vault with the absolute path to your local vault directory.
Step 3. Fully quit and reopen Claude Desktop. The vault tools will appear automatically.
Don't have a vault yet? Copy the included template:
cp -r example_vault /Users/yourname/my-vault
Updating to the Latest Version
When a new version is released, pull the latest image before restarting Claude Desktop:
docker pull ghcr.io/oliverxuzy-ai/obsidian-in-a-vat:latest
Alternative Setup (Python / uv)
If you prefer not to use Docker:
# Install
uv venv && source .venv/bin/activate
uv pip install -e .
Claude Desktop config:
{
"mcpServers": {
"vault": {
"command": "/absolute/path/to/.venv/bin/python",
"args": ["-m", "vault_mcp"],
"env": {
"VAULT_LOCAL_PATH": "/Users/yourname/my-vault"
}
}
}
}
Use the absolute path to the venv's python — Claude Desktop does not inherit your shell PATH.
Tools
| Tool | Actions | Description |
|---|---|---|
vault_read | search, get, list_captures | Search vault, read files, list captures by status |
vault_capture | save, delete | Capture refined insights with auto-tagging, or delete captures |
vault_promote | promote | Promote captures into structured notes with auto-wikilinks |
vault_analyze | rebuild_graph, clusters, connections, orphans | Knowledge graph: build graph, Louvain clustering, N-degree connections, orphan detection |
vault_topic | prepare, create, update | Topic lifecycle: gather materials (progressive disclosure), create/update MOC-style topics |
Auto-Tag Extraction
Tags are extracted from capture text using three sources (in priority order):
- tags.yaml — Custom tags and synonym mappings at the vault root
- Existing notes — Tags collected from existing vault files' frontmatter
- Default domains — Fallback: ai, llm, productivity, writing, coding, design, business, learning, health, finance, philosophy, psychology
Example tags.yaml in your vault root:
tags:
ai: [artificial intelligence, machine learning, ML, deep learning]
coding: [programming, software, development, code]
design: [UX, UI, user experience]
Development
# Build image locally
docker build -t vault-mcp .
# Test the container starts (Ctrl+C to stop)
echo '{}' | docker run -i --rm -v $(pwd)/example_vault:/vault vault-mcp
# Syntax check
python -m py_compile src/vault_mcp/server.py
# Interactive MCP Inspector
mcp dev src/vault_mcp/server.py
中文
个人知识库 MCP 服务器,适配 Claude Desktop。捕获想法、搜索笔记、读取本地 markdown 知识库中的文件。
快速开始(Docker — 推荐)
第一步. 确保 Docker Desktop 正在运行。
第二步. 添加到 Claude Desktop 配置文件(~/Library/Application Support/Claude/claude_desktop_config.json):
{
"mcpServers": {
"vault": {
"command": "docker",
"args": [
"run", "-i", "--rm",
"-v", "/Users/yourname/my-vault:/vault",
"ghcr.io/oliverxuzy-ai/obsidian-in-a-vat:latest"
]
}
}
}
将 /Users/yourname/my-vault 替换为你本地 vault 目录的绝对路径。
第三步. 完全退出并重新打开 Claude Desktop,vault 工具会自动出现。
还没有 vault? 复制内置模板:
cp -r example_vault /Users/yourname/my-vault
更新到最新版本
当有新版本发布时,在重启 Claude Desktop 前先拉取最新镜像:
docker pull ghcr.io/oliverxuzy-ai/obsidian-in-a-vat:latest
备选安装方式(Python / uv)
如果不想使用 Docker:
# 安装
uv venv && source .venv/bin/activate
uv pip install -e .
Claude Desktop 配置:
{
"mcpServers": {
"vault": {
"command": "/绝对路径/.venv/bin/python",
"args": ["-m", "vault_mcp"],
"env": {
"VAULT_LOCAL_PATH": "/Users/yourname/my-vault"
}
}
}
}
必须使用 venv 内 python 的绝对路径 — Claude Desktop 不继承你的 shell PATH。
工具
| 工具 | Actions | 说明 |
|---|---|---|
vault_read | search, get, list_captures | 搜索 vault、读取文件、按状态列出 captures |
vault_capture | save, delete | 捕获精炼洞察并自动打标签,或删除 capture |
vault_promote | promote | 将 captures 提升为结构化笔记,自动插入 wikilinks |
vault_analyze | rebuild_graph, clusters, connections, orphans | 知识图谱:构建图谱、Louvain 聚类、N 度关联查询、孤岛检测 |
vault_topic | prepare, create, update | Topic 生命周期:收集原材料(渐进式披露)、创建/更新 MOC 结构笔记 |
自动标签提取
标签从 capture 文本中提取,使用三个来源(按优先级排序):
- tags.yaml — vault 根目录的自定义标签和同义词映射
- 已有笔记 — 收集已有 vault 文件 frontmatter 中的标签进行匹配
- 默认领域 — 兜底列表:ai, llm, productivity, writing, coding, design, business, learning, health, finance, philosophy, psychology
tags.yaml 示例(放在 vault 根目录):
tags:
ai: [artificial intelligence, machine learning, ML, deep learning]
coding: [programming, software, development, code]
design: [UX, UI, user experience]
开发
# 本地构建镜像
docker build -t vault-mcp .
# 测试容器启动(Ctrl+C 停止)
echo '{}' | docker run -i --rm -v $(pwd)/example_vault:/vault vault-mcp
# 语法检查
python -m py_compile src/vault_mcp/server.py
# 使用 MCP Inspector 交互测试
mcp dev src/vault_mcp/server.py
関連サーバー
MD-PDF MCP Server
A server for converting Markdown files to PDF format. Requires pandoc and weasyprint.
DaVinci Resolve
Enables AI assistants to interact with DaVinci Resolve Studio for advanced control over video editing, color grading, and audio.
MCP Data Analizer
Analyze and visualize data from .xlsx and .csv files using matplotlib and plotly.
MCBU Campus Assistant
A chatbot for Manisa Celal Bayar University student affairs, featuring a web scraper, student database, and API integration tools for automation.
Panda Odoo
An MCP server for integrating with the Odoo ERP system.
Google Workspace
Manage Gmail, Calendar, Drive, and Contacts through Google Workspace APIs using OAuth 2.0.
Google Workspace
Integrates Google Workspace services like Calendar, Drive, and Gmail with AI assistants.
Pantry Persona
AI-powered kitchen management - track pantry inventory, plan meals, manage recipes, build shopping lists
Jira
Interact with Jira to manage issues, projects, and workflows using the Jira Cloud Platform REST API.
MIE - Memory Intelligence Engine
Persistent knowledge graph MCP server that gives AI agents shared memory across sessions and providers. Stores facts, decisions, entities, and events with typed relationships.