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Agent Skill · 研究检索

obsidian-semantic-search(Obsidian semantic 搜索)

obsidian-semantic-search 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

obsidian-semantic-search 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 17,051。

总安装 6,830周安装 279GitHub Stars 1下载 2,187核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.1

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:obsidian-semantic-search(Obsidian semantic 搜索)
来源仓库:https://github.com/celstnblacc/obsidian-semantic-search
安装命令:
openclaw skills install obsidian-semantic-search
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install obsidian-semantic-search

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

使用本地嵌入技术对 Obsidian 金库进行语义搜索,支持混合、语义和关键字检索。适合在知识库中快速定位相关笔记,提升信息查找效率。通过 MCP 工具实现文件操作与批量读取,支持多种查询方式组合使用。安装命令:openclaw skills install obsidian-semantic-search。

需确认 Ollama 和 pgvector 环境配置及文件访问权限。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install obsidian-semantic-search;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

obsidian-semantic-search 怎么安装?

在终端执行 openclaw skills install obsidian-semantic-search。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

obsidian-semantic-search 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

obsidian-semantic-search 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

obsidian-semantic-search 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

obsidian-semantic-search 用的人多吗?

公开数据是累计安装 6,830 次,近一周安装 279 次,下载 2,187 次,GitHub 1 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

obsidian-semantic-search 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
obsidian-semantic-search

Obsidian semantic 搜索 · 本页

6,8301接触敏感数据MIT-0有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
Obsidian Semantic Search
description
Semantic search across your Obsidian vaults using local embeddings (Ollama + pgvector). 10 MCP tools: hybrid/semantic/keyword search, file CRUD, batch reads, live re-indexing, and a monitoring dashboard. Fully local — no API keys, no cloud, zero cost.
version
1.0.0
emoji
🧠
homepage
https://github.com/celstnblacc/obsidian-semantic-mcp
user-invocable
true
disable-model-invocation
false
requires
bins
["docker", "uv"]
anyBins
["python3", "python"]
env
["OBSIDIAN_VAULT"]

Obsidian Semantic Search

Search your Obsidian vault by meaning, not just keywords. This skill installs and configures obsidian-semantic-mcp — a local-first MCP server that indexes your vault with vector embeddings (Ollama + pgvector) and exposes 10 tools to any MCP-compatible AI assistant.

What You Get

10 MCP Tools

ToolWhat it does
search_vaultSemantic, keyword, or hybrid search with similarity scores
simple_searchFast exact-text search across all files
list_filesBrowse vault directories
get_fileRead a single file
get_files_batchRead multiple files in one call
append_contentAppend text to a file (creates if missing)
write_fileOverwrite a file completely
recent_changesList recently modified files
list_indexed_notesSee all indexed notes with timestamps
reindex_vaultForce a full re-index

Monitoring Dashboard (port 8484)

  • Real-time service health (PostgreSQL, Ollama, embedding model)
  • Indexed notes count, vault coverage %, database size
  • Search testing UI — test queries without leaving your browser
  • Manual re-index trigger

Search Modes

  • Hybrid (default): Combines semantic meaning + keyword matching for best results
  • Semantic: Search by meaning only — finds related content even with different wording
  • Keyword: Exact text matching via PostgreSQL full-text search

Installation

Prerequisites

  • Docker Desktop (running)
  • uv (Python package manager): curl -LsSf https://astral.sh/uv/install.sh | sh
  • An Obsidian vault on your local filesystem

One-Liner Install

bash <(curl -fsSL https://raw.githubusercontent.com/celstnblacc/obsidian-semantic-mcp/main/install.sh) --mode 2 --vault /path/to/your/vault

This clones the repo to ~/.local/share/obsidian-semantic-mcp, installs the osm CLI, and runs the setup wizard in Docker mode.

Manual Install

git clone https://github.com/celstnblacc/obsidian-semantic-mcp.git
cd obsidian-semantic-mcp
uv sync
uv run osm init

The wizard detects your OS and offers setup modes:

macOS (4 modes):

  • Mode 1: Native (Homebrew — no Docker needed)
  • Mode 2: Docker + host Ollama (if Ollama already installed)
  • Mode 3: Full Docker (recommended — everything in containers)
  • Mode 4: Docker + remote Ollama (SSH tunnel to a GPU server)

Linux (3 modes):

  • Mode 1: Docker + host Ollama
  • Mode 2: Full Docker (recommended)
  • Mode 3: Docker + remote Ollama

Verify Installation

osm status

Should show: Docker containers running, Ollama healthy, embedding model loaded, vault indexed.

Register with Claude Desktop

The wizard auto-configures this, but if you need to do it manually:

Add to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or ~/.config/Claude/claude_desktop_config.json (Linux):

{
  "mcpServers": {
    "obsidian-semantic": {
      "command": "docker",
      "args": ["exec", "-i", "obsidian-semantic-mcp-mcp-server-1", "python3", "src/server.py"]
    }
  }
}

Restart Claude Desktop after adding.

Configuration

Set these in .env or as environment variables:

VariableRequiredDefaultNotes
OBSIDIAN_VAULTYes—Path to your vault
OBSIDIAN_VAULTSNo—Comma-separated paths for multi-vault
POSTGRES_PASSWORDYes (Docker)—Database password
EMBEDDING_MODELNonomic-embed-textOllama model (~7GB)
RERANK_MODELNo—Optional cross-encoder for better ranking
DASHBOARD_PORTNo8484Monitoring dashboard port

Usage Examples

Once installed, your AI assistant can use these tools naturally:

Semantic search:

"Search my vault for notes about authentication patterns" → Uses search_vault with hybrid mode, returns top 5 matches ranked by meaning

Find and read:

"Find my meeting notes from last week and summarize them" → Uses recent_changes to find files, get_files_batch to read them

Append to a note:

"Add this action item to my project-x.md file" → Uses append_content to add text without overwriting

Re-index after bulk changes:

"I just reorganized my vault, re-index everything" → Uses reindex_vault to rebuild the full index

Maintenance

osm status       # Check health
osm rebuild      # Rebuild Docker images after updates
osm remove       # Stop and clean up everything

Architecture

  • PostgreSQL 17 + pgvector: Stores 768-dim vector embeddings, IVFFlat index for fast cosine similarity search
  • Ollama (nomic-embed-text): Local embedding model — no API keys, no cloud calls
  • Watchdog file watcher: Auto-re-indexes when vault files change (0.5s debounce)
  • LRU cache: 256 entries, 10-min TTL — skips redundant Ollama calls for repeated queries

Troubleshooting

ProblemFix
"Ollama not responding"Run osm status — if Ollama is down, the dashboard has a "Start Ollama" button
Slow first searchFirst query loads the model into memory (~5s). Subsequent queries are <1s
Missing notes in searchRun osm status to check indexing coverage. Use dashboard to trigger re-index
Docker errorsEnsure Docker Desktop is running. Try osm rebuild to rebuild images
VirusTotal "suspicious" warning on installThis is a false positive — the skill *describes* searching vault content, which triggers pattern detection. Use clawhub install obsidian-semantic-search --force to proceed. The skill is MIT-0 licensed and contains no executable code beyond documentation.

Links

  • Source: https://github.com/celstnblacc/obsidian-semantic-mcp
  • Changelog: https://github.com/celstnblacc/obsidian-semantic-mcp/blob/main/CHANGELOG.md
  • Architecture: https://github.com/celstnblacc/obsidian-semantic-mcp/blob/main/docs/ARCHITECTURE.md
  • License: Apache 2.0 (source repo) / MIT-0 (this skill)

*Built by celstnblacc — 207 unit tests, Docker + native install, multi-vault support.*

平台分布

OpenClaw

97.67%
按下载量换算2,136

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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