# EzRAG MCP Server

> Use this tool when you need to integrate external AI agents with Obsidian notes, enabling semantic and keyword searches to retrieve specific notes from a vault. It solves problems of note discovery and access, allowing AI agents to query and fetch relevant information. The EzRAG MCP Server takes search queries as input and returns relevant notes as output, ideal for use cases requiring automated note retrieval and analysis.

Canonical page: https://skillsregistry.net/skills/benbjurstrom-ezrag  
JSON: https://api.skillsregistry.net/v1/skills/benbjurstrom-ezrag

## Description

Provides semantic search and keyword search over Obsidian notes, along with direct note retrieval, allowing external AI agents to query and access the vault.

## Trust

- **Trust score (0–1):** 0.85
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-19

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/owiizlb4cr)
- **Repository:** <https://github.com/benbjurstrom/ezrag>

## 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": "benbjurstrom-ezrag"
    }
  }
}
```

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