Obsidian MCP: AI-Powered Note Automation & Smart Workflows

Obsidian MCP bridges AI models to your vaults, letting them effortlessly read, edit, create, and organize notes—smarter workflows, no coding Required. 🚀" )

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About Obsidian MCP

What is Obsidian MCP: AI-Powered Note Automation & Smart Workflows?

Obsidian MCP is a server implementation of the Model Context Protocol (MCP) designed to bridge AI models with Obsidian knowledge bases. It enables AI systems to programmatically interact with notes and folders within Obsidian vaults, automating workflows like content creation, search, and organization. For example, a researcher could use this tool to automatically tag and categorize hundreds of academic papers in their vault based on AI-driven analysis.

How to use Obsidian MCP: AI-Powered Note Automation & Smart Workflows?

Implementation follows three core steps: setup, configuration, and integration. First install Node.js and the Obsidian Local REST API plugin. Configure the server by specifying your vault path and API credentials in the .env file. Run the server via npm start, then connect your AI model to communicate through standard I/O channels. This process creates a direct pipeline for AI systems to execute actions like "search for all notes mentioning 'climate change' from 2023".

Obsidian MCP Features

Key Features of Obsidian MCP: AI-Powered Note Automation & Smart Workflows?

End-to-end automation: Full CRUD (Create/Read/Update/Delete) operations on notes and folders
Context-aware search: Advanced semantic search across entire vaults
Structural control: Programmatic folder management including nesting and renaming
Protocol compliance: Adherence to MCP standards for interoperability with AI frameworks
Development-friendly: Hot-reloading in dev mode and modular code structure

Use cases of Obsidian MCP: AI-Powered Note Automation & Smart Workflows?

Practical applications include:

Auto-tagging notes based on content using NLP models
Generating cross-references between related documents
Maintaining versioned knowledge bases with AI-assisted edits
Building chatbots that query Obsidian data in real-time
Automating periodic reports by aggregating vault content

Obsidian MCP FAQ

FAQ from Obsidian MCP: AI-Powered Note Automation & Smart Workflows?

Q: Does this require specific Obsidian plugins?
A: Yes, the Local REST API plugin is mandatory for vault access
Q: How secure is the setup?
A: API tokens are required and vault paths are restricted to user-specified directories
Q: Can I use this with cloud-based Obsidian?
A: Currently supports only local vaults via the desktop app
Q: What AI models are compatible?
A: Any MCP-compliant model, including Anthropic's Claude series

Content

Obsidian MCP (Model Context Protocol) 服务器

English | 中文

这个项目实现了一个 Model Context Protocol (MCP) 服务器，用于连接 AI 模型与 Obsidian 知识库。通过这个服务器，AI 模型可以直接访问和操作 Obsidian 笔记，包括读取、创建、更新和删除笔记，以及管理文件夹结构。

功能特点

与 Obsidian 知识库的无缝集成
支持笔记的读取、创建、更新和删除
支持文件夹的创建、重命名、移动和删除
支持全文搜索功能
符合 Model Context Protocol 规范

前提条件

Node.js (v16 或更高版本)
Obsidian 桌面应用
Obsidian Local REST API 插件 (需要在 Obsidian 中安装)

安装

克隆此仓库：

bash git clone https://github.com/newtype-01/obsidian-mcp.git cd obsidian-mcp

安装依赖：

bash npm install

构建项目：

bash npm run build

配置

服务器通过环境变量进行配置：

OBSIDIAN_VAULT_PATH: Obsidian 知识库的路径
OBSIDIAN_API_TOKEN: Obsidian Local REST API 插件的 API 令牌
OBSIDIAN_API_PORT: Obsidian Local REST API 插件的端口号 (默认为 27123)

您可以通过以下方式设置环境变量：

复制 .env.example 文件为 .env 并编辑其中的值：

bash cp .env.example .env

编辑 .env 文件，填入您的实际配置：

OBSIDIAN_VAULT_PATH=/path/to/your/vault OBSIDIAN_API_TOKEN=your_api_token_here OBSIDIAN_API_PORT=27123

注意： .env 文件包含敏感信息，已被添加到 .gitignore 中，不会被提交到版本控制系统。

使用方法

确保 Obsidian 正在运行，并且已安装和配置了 Local REST API 插件
启动 MCP 服务器：

bash npm start

服务器将通过标准输入/输出与 AI 模型通信

测试

项目包含一个测试脚本，用于验证服务器功能：

bash node test-mcp.js

支持的工具

MCP 服务器提供以下工具：

list_notes: 列出知识库中的所有笔记
read_note: 读取指定笔记的内容
create_note: 创建新笔记
update_note: 更新现有笔记
search_vault: 在知识库中搜索内容
delete_note: 删除笔记
manage_folder: 管理文件夹 (创建、重命名、移动、删除)

开发

使用 npm run dev 在开发模式下运行服务器
源代码位于 src 目录中

许可证

ISC

贡献

欢迎提交 Pull Requests 和 Issues！