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Obsidian Semantic Search

作者:DalecB版本 0.2.1i★ –i在你的电脑上运行
注册名称io.github.DalecB/obsidian-semantic-mcp

安装

概览

作者提供的说明(英文原文)

Read-only semantic search MCP server for Obsidian vaults using local Ollama embeddings.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 文档、表格与办公
  • 你需要填写:OBSIDIAN_VAULT_ROOT

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 需要你自己填写: OBSIDIAN_VAULT_ROOT, OBSIDIAN_SEMANTIC_MCP_HOME, OBSIDIAN_EMBED_MODEL, OLLAMA_BASE_URL, OBSIDIAN_SEMANTIC_STARTUP_INDEX, OBSIDIAN_SEMANTIC_ALLOW_SENSITIVE, OBSIDIAN_SEMANTIC_EXCLUDE, OBSIDIAN_SEMANTIC_SENSITIVE_PATHS

你需要

  • npm已安装 Node.js(用于 npx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "obsidian-semantic": {
      "command": "npx",
      "args": [
        "-y",
        "@dalecb/obsidian-semantic-mcp"
      ],
      "env": {
        "OBSIDIAN_VAULT_ROOT": "your-value",
        "OBSIDIAN_SEMANTIC_MCP_HOME": "your-value",
        "OBSIDIAN_EMBED_MODEL": "your-value",
        "OLLAMA_BASE_URL": "your-value",
        "OBSIDIAN_SEMANTIC_STARTUP_INDEX": "your-value",
        "OBSIDIAN_SEMANTIC_ALLOW_SENSITIVE": "your-value",
        "OBSIDIAN_SEMANTIC_EXCLUDE": "your-value",
        "OBSIDIAN_SEMANTIC_SENSITIVE_PATHS": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add obsidian-semantic --env OBSIDIAN_VAULT_ROOT=your-value --env OBSIDIAN_SEMANTIC_MCP_HOME=your-value --env OBSIDIAN_EMBED_MODEL=your-value --env OLLAMA_BASE_URL=your-value --env OBSIDIAN_SEMANTIC_STARTUP_INDEX=your-value --env OBSIDIAN_SEMANTIC_ALLOW_SENSITIVE=your-value --env OBSIDIAN_SEMANTIC_EXCLUDE=your-value --env OBSIDIAN_SEMANTIC_SENSITIVE_PATHS=your-value -- npx -y @dalecb/obsidian-semantic-mcp

运行前请先填写空着的值。

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "obsidian-semantic": {
      "command": "npx",
      "args": [
        "-y",
        "@dalecb/obsidian-semantic-mcp"
      ],
      "env": {
        "OBSIDIAN_VAULT_ROOT": "your-value",
        "OBSIDIAN_SEMANTIC_MCP_HOME": "your-value",
        "OBSIDIAN_EMBED_MODEL": "your-value",
        "OLLAMA_BASE_URL": "your-value",
        "OBSIDIAN_SEMANTIC_STARTUP_INDEX": "your-value",
        "OBSIDIAN_SEMANTIC_ALLOW_SENSITIVE": "your-value",
        "OBSIDIAN_SEMANTIC_EXCLUDE": "your-value",
        "OBSIDIAN_SEMANTIC_SENSITIVE_PATHS": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "obsidian-semantic": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@dalecb/obsidian-semantic-mcp"
      ],
      "env": {
        "OBSIDIAN_VAULT_ROOT": "your-value",
        "OBSIDIAN_SEMANTIC_MCP_HOME": "your-value",
        "OBSIDIAN_EMBED_MODEL": "your-value",
        "OLLAMA_BASE_URL": "your-value",
        "OBSIDIAN_SEMANTIC_STARTUP_INDEX": "your-value",
        "OBSIDIAN_SEMANTIC_ALLOW_SENSITIVE": "your-value",
        "OBSIDIAN_SEMANTIC_EXCLUDE": "your-value",
        "OBSIDIAN_SEMANTIC_SENSITIVE_PATHS": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

需要你填写的值

  • OBSIDIAN_VAULT_ROOT 必填 env
    Absolute path to the local Obsidian vault.
  • OBSIDIAN_SEMANTIC_MCP_HOME env
    Directory for the external SQLite index, logs, and cache.
  • OBSIDIAN_EMBED_MODEL env
    Ollama embedding model name. Defaults to bge-m3.
  • OLLAMA_BASE_URL env
    Ollama API base URL. Defaults to http://localhost:11434.
  • OBSIDIAN_SEMANTIC_STARTUP_INDEX env
    Set to true to run incremental indexing when the server starts.
  • OBSIDIAN_SEMANTIC_ALLOW_SENSITIVE env
    Set to true to allow include_sensitive tool calls.
  • OBSIDIAN_SEMANTIC_EXCLUDE env
    Comma- or newline-separated folders to always exclude from indexing, search, and read.
  • OBSIDIAN_SEMANTIC_SENSITIVE_PATHS env
    Comma- or newline-separated folders treated as sensitive (blocked unless unlocked). Defaults to 08_PersonalInfo/.

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 DalecB 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“文档、表格与办公”中的其他服务器比较i

  • 星标数多于此分类中其他 2197 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 2197 个服务器的 12% 更新
  • 基础检查结果等于或优于此分类中其他 2197 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Obsidian Semantic Search 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

你需要填写:OBSIDIAN_VAULT_ROOT

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.2.1)于5个月前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js。

有什么可以替代它?

同一分类中有:Agent-Native Calendar, Excel MCP Server, MCP Server for Excel

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Agent-Native Calendar

作者:BuilderIO

Agent-Native Google Calendar - manage events, sync, and public booking

在云端运行★ 7,620MIT2个月前更新
安装

Excel MCP Server

作者:haris-musa

Create and edit Excel files with AI: charts, PivotTables, formulas. No Excel needed.

在你的电脑上运行★ 4,276MIT6天前更新
安装

MCP Server for Excel

作者:sbroenne

Excel automation for AI - Sheets, Power Query, DAX, VBA, Tables, Ranges and more. Windows only.

在你的电脑上运行★ 847MIT4天前更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

Obsidian Semantic Search MCP

Read-only semantic retrieval for agents that need to find the right Obsidian note without write access.

한국어 · Quick Start · Why This Exists · How It Works


Your Obsidian vault is useful only if your agent can find the right note.

Keyword search misses context. Full write-capable Obsidian MCP servers expose more power than a retrieval agent needs. Obsidian plugins are great inside Obsidian, but they are not always the right boundary for Codex, Claude Desktop, Cursor, or any other MCP client.

This project is the narrow version:

local Obsidian vault -> read-only scanner -> local SQLite index -> MCP search/read tools

No note writes. No cloud embeddings by default. No Obsidian plugin runtime. No sync service.

Status: 0.3.1 early preview. The server is usable today, but ranking behavior and tool schemas may change before 1.0.

What You Get

NeedWhat this server does
Find the note an agent should readHybrid semantic + keyword search over Markdown notes
Keep the vault safeExposes search/read/index/status only; no write, patch, move, rename, or delete tools
Stay local-firstUses Ollama embeddings and stores the index on your machine
Make results agent-friendlyReturns file-level matches with headings, snippets, and line ranges
Avoid plugin stateReads the vault directly from the filesystem; Obsidian does not need to be running

Example result shape:

{

"path": "02_Projects/RealtimeAPI/05_Interview_QA.md", "title": "Interview Q&A", "score": 0.7431, "matched_sections": [ { "heading": "Level 4 > Redis Lua atomicity", "lines": [266, 305], "reason": "semantic=1, keyword=0.5565, metadata=0.6" } ] }

Quick Start

Requirements:

  • Node.js >= 24
  • Ollama
  • An Obsidian vault
  • An MCP client such as Codex, Claude Desktop, Cursor, or another stdio MCP client

Install the embedding model:

ollama pull bge-m3

curl http://localhost:11434/api/tags

Print setup guidance:

npx -y --package @dalecb/obsidian-semantic-mcp obsidian-semantic-mcp-setup

Codex Setup

Add this to ~/.codex/config.toml:

[mcp_servers.obsidian_semantic]

command = "npx" args = ["-y", "@dalecb/obsidian-semantic-mcp"]

[mcp_servers.obsidian_semantic.env] OBSIDIAN_VAULT_ROOT = "/path/to/your/Obsidian Vault" OBSIDIAN_SEMANTIC_MCP_HOME = "/Users/you/.obsidian-semantic-mcp" OLLAMA_BASE_URL = "http://localhost:11434" OBSIDIAN_EMBED_MODEL = "bge-m3" OBSIDIAN_SEMANTIC_AUTO_INDEX = "true"

Restart Codex, then run:

obsidian_semantic.index_status

obsidian_semantic.search_notes { "query": "Redis Lua atomicity", "limit": 5 }

Claude Code Setup

Add the server at user scope so the personal vault path stays out of project .mcp.json files:

claude mcp add obsidian_semantic --scope user \

--env OBSIDIAN_VAULT_ROOT="/path/to/your/Obsidian Vault" \ --env OBSIDIAN_SEMANTIC_MCP_HOME="/Users/you/.obsidian-semantic-mcp" \ --env OLLAMA_BASE_URL="http://localhost:11434" \ --env OBSIDIAN_EMBED_MODEL="bge-m3" \ --env OBSIDIAN_SEMANTIC_AUTO_INDEX="true" \ -- npx -y @dalecb/obsidian-semantic-mcp

claude mcp get obsidian_semantic

Start a new Claude Code session and run /mcp to confirm the server is connected. On native Windows, use -- cmd /c npx -y @dalecb/obsidian-semantic-mcp after the environment flags.

See Anthropic's Claude Code MCP documentation for scope and command details.

Claude Desktop / JSON MCP Client Setup

In Claude Desktop, open Settings → Developer → Edit Config. This opens ~/Library/Application Support/Claude/claude_desktop_config.json on macOS or %APPDATA%\Claude\claude_desktop_config.json on Windows. Merge the following server into mcpServers:

{

"mcpServers": { "obsidian_semantic": { "command": "npx", "args": ["-y", "@dalecb/obsidian-semantic-mcp"], "env": { "OBSIDIAN_VAULT_ROOT": "/path/to/your/Obsidian Vault", "OBSIDIAN_SEMANTIC_MCP_HOME": "/Users/you/.obsidian-semantic-mcp", "OLLAMA_BASE_URL": "http://localhost:11434", "OBSIDIAN_EMBED_MODEL": "bge-m3", "OBSIDIAN_SEMANTIC_AUTO_INDEX": "true" } } } }

Fully quit and restart Claude Desktop. Cursor and other JSON-style stdio MCP clients can use the same mcpServers entry. On Windows, if npx is not found, use "command": "cmd" and prepend "/c", "npx" to args.

See the official local MCP server guide for Claude Desktop configuration and logs.

Why This Exists

This isn't aiming to be the most powerful Obsidian automation server. It aims to be the safest retrieval tool you can hand an agent.

Here's how it stacks up against the two tools it usually comes down to — a full-permission Obsidian MCP server (Local REST API based) and GBrain (a broader knowledge-compilation platform):

This projectFull-permission Obsidian MCPGBrain
Access modelRead-only: search / read / indexRead + write + edit + deleteRead + write; compiles notes into its own model
Touches your vaultNeverYesYes — restructures content
Obsidian must runNo — reads files directlyYes — needs the REST API pluginNo
Required local runtimeNode.js + OllamaObsidian + pluginStandalone platform
Embeddings & dataLocal Ollama by default; remote URL is configurableLocal API; embeddings vary by setupBuilt-in pipeline; optional sync
StorageOne SQLite file you can delete and rebuildPlugin-managedIts own store / migration
Best forA small read-only retrieval boundary for agentsFull vault automation and editingBuilding a compiled knowledge base across sources

That trade is on purpose: give up writing, editing, and running inside Obsidian, and you get fewer moving parts and a smaller blast radius in return.

Use this if your agent should answer:

  • "Which note explains this project decision?"
  • "Find the file where I wrote about idempotency payload mismatch."
  • "Show me the career notes related to this interview topic."
  • "Search my vault, but do not mutate it."

Do not use this if you want an Obsidian UI plugin, automatic note generation, or write-capable vault automation.

Tools

index_status

Returns index metadata and safety settings.

index_vault

Builds or updates the external SQLite index.

{ "mode": "incremental" }

Specific files:

{

"mode": "incremental", "paths": ["02_Projects/My Note.md"] }

search_notes

Searches notes with hybrid semantic and keyword ranking.

{

"query": "live coding notes", "limit": 8, "mode": "hybrid" }

Modes:

  • hybrid: semantic vector + SQLite FTS5 + metadata boosts
  • semantic: vector-first search
  • keyword: FTS5 keyword search without embedding the query
read_note

Reads a note or line range by vault-relative path.

{

"path": "02_Projects/My Note.md", "start_line": 10, "end_line": 40 }

How It Works

index_vault

-> scan Markdown files under OBSIDIAN_VAULT_ROOT -> block denied paths and symlink escapes -> split notes by Markdown headings -> create one summary chunk per file -> embed chunks with Ollama bge-m3 -> store notes, chunks, FTS rows, and vectors in SQLite

search_notes -> incrementally index on first search or first search after a Markdown change -> embed the query with Ollama -> score vector similarity -> score SQLite FTS5 keyword matches -> apply title/path/heading metadata boosts -> regroup chunk matches into file-level results

Default storage:

~/.obsidian-semantic-mcp/

data/semantic.sqlite

The vault remains the source of truth. The SQLite database is a derived index and can be deleted/rebuilt.

Safety Model

The server reads your vault and never writes to it. Three layers decide what an agent can see.

1. Always denied (system / tooling). Never indexed, no override:

  • .obsidian/, .smart-env/, .claude/, .codex-*/
  • any hidden folder (name starts with .)
  • node_modules, cache, logs

2. Sensitive — denied by default, unlockable. Stays blocked even when a tool call passes include_sensitive: true, unless the server is started with OBSIDIAN_SEMANTIC_ALLOW_SENSITIVE=true. Defaults to 08_PersonalInfo/. Override the list with OBSIDIAN_SEMANTIC_SENSITIVE_PATHS (comma- or newline-separated folders):

OBSIDIAN_SEMANTIC_SENSITIVE_PATHS = "08_PersonalInfo, 09_Finance"

3. Your own excludes — always denied. Folders you never want indexed, searched, or read. No unlock flag:

OBSIDIAN_SEMANTIC_EXCLUDE = "03_Journal, Private, Clients/Acme"

Which one do you want?

  • "Don't index this at all" → OBSIDIAN_SEMANTIC_EXCLUDE
  • "Keep it locked, but I can unlock it with a flag when I need to" → OBSIDIAN_SEMANTIC_SENSITIVE_PATHS + OBSIDIAN_SEMANTIC_ALLOW_SENSITIVE

Additional guards:

  • All paths are resolved through realpath.
  • Path traversal and URL-encoded traversal are blocked.
  • Symlinks that escape the vault root or point to a denied in-vault path are blocked.

search_notes and read_note enforce the current exclusion settings on every call. With automatic indexing enabled, the next search also removes excluded stale rows from the index. Confirm the active lists with index_status.

The local index stores snippets and embedding vectors. Treat it as a derived copy of your vault. See PRIVACY.md.

Indexing Strategy

The default is action-driven, not timer-based:

  1. The first search_notes after server start.
  2. The first search_notes after a Markdown create, update, delete, or rename event.
  3. The first search_notes after the embedding model or index format changes; this triggers a full rebuild.
  4. An explicit index_vault call.

The filesystem watcher only marks the index dirty. Indexing runs once, immediately before the next search, and concurrent searches share that work. If recursive watching is unavailable, the server falls back to an incremental scan before every search.

Disable automatic indexing with:

OBSIDIAN_SEMANTIC_AUTO_INDEX = "false"

Then call index_vault { "mode": "incremental" } yourself. The legacy OBSIDIAN_SEMANTIC_STARTUP_INDEX=true remains supported, but is not the default because it does work even when no search follows.

Search Quality Evaluation

Create a JSON file containing queries and expected paths to compare keyword, semantic, and hybrid modes under the same conditions:

[

{ "query": "strong consistency at 1000 TPS", "expected_paths": ["03_Knowledge/QnA/Strong-Consistency-at-1000TPS.md"] } ]

npm run evaluate --

只显示了开头部分;其余内容请在仓库中阅读

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