# Obsidian

> Use this tool when you need to efficiently explore and analyze personal knowledge bases stored in Obsidian's markdown format. It provides read-only access to Obsidian vaults, solving problems such as note discovery and metadata retrieval through searching, retrieving, and listing markdown files. With inputs including vault paths and search queries, and outputs including note content and metadata, it is ideal for use cases involving knowledge base organization and research.

Canonical page: https://skillsregistry.net/skills/mikesusz-obsidian  
JSON: https://api.skillsregistry.net/v1/skills/mikesusz-obsidian

## Description

Provides read-only access to Obsidian vaults through three core tools: searching notes by content or title with contextual excerpts, retrieving full note content and metadata by path, and listing all markdown files optionally filtered by subfolder. Built in Python with frontmatter parsing support for exploring and analyzing personal knowledge bases stored in Obsidian's markdown format.

## Trust

- **Trust score (0–1):** 0.97
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** search
- **Updated:** 2026-09-28

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/mikesusz-obsidian)
- **Repository:** <https://github.com/mikesusz/markdown-vault-mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "mikesusz-obsidian"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/mikesusz-obsidian` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/mikesusz-obsidian/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt