# ZIM RAG MCP Server

> Use this tool when you need to interact with .zim archives and perform semantic searches on their content. It solves problems related to article discovery, content retrieval, and metadata extraction from compressed ZIM files. The tool takes .zim archives as input and provides search results, article content, and metadata as output, making it ideal for applications requiring efficient information retrieval from large archives.

Canonical page: https://skillsregistry.net/skills/gglessner-zim-mcp  
JSON: https://api.skillsregistry.net/v1/skills/gglessner-zim-mcp

## Description

Enables interaction with .zim archives by providing tools for article search, content retrieval, and metadata discovery. It features a TF-IDF based RAG engine for semantic retrieval over extracted article chunks from compressed ZIM files.

## Trust

- **Trust score (0–1):** 0.91
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

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

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/fk4z9qq23d)
- **Repository:** <https://github.com/gglessner/ZIM-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": "gglessner-zim-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/gglessner-zim-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/gglessner-zim-mcp/pull`

---
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