Skip to main content

MCP server that enables AI models to access and search ZIM format knowledge bases offline

Project description

English | 中文

ZIM MCP Server

ZIM (Zeno IMproved) is a file format developed by the nonprofit organization Kiwix, designed specifically for offline storage and access to Wikipedia and other large reference content. The ZIM format supports high compression rates and fast searching, enabling entire Wikipedia content to be compressed into relatively small files for convenient storage and use, especially in environments without internet connectivity.

ZIM MCP Server provides large language models with the ability to directly access and search content within ZIM files, allowing people to use local AI models for question answering and information retrieval from these offline knowledge resources, even without network access.

About Kiwix

Kiwix is a nonprofit organization dedicated to making online knowledge content (especially Wikipedia, TED talks, etc.) accessible offline. Kiwix has developed tools for creating, viewing, and searching ZIM files, through which people can package large amounts of online knowledge resources into ZIM files for local access. The Kiwix project is particularly important for developing countries and regions without internet connectivity, as it enables people in these areas to access rich knowledge resources, promoting the dissemination of knowledge and equal educational opportunities.

Installation

1. Clone the Repository

git clone https://github.com/ThinkInAI-Hackathon/zim-mcp-server.git

2. Install uv

  • On Windows:
    • If you have not set execution policy before, run:
      powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
      
    • Otherwise, you can run:
      irm https://astral.sh/uv/install.ps1 | iex
      
  • On MacOS:

3. Install Dependencies

cd path\to\zim-mcp-server   # (e.g., D:\zim-mcp-server)
uv sync

4. Prepare ZIM Files

Download ZIM files (e.g., Wikipedia, Wiktionary, etc.) from the Kiwix Library and place them in a directory, e.g.,

path\to\zim\files   # (e.g., D:\ZIM)

Configuration for Claude Desktop

The configuration for Claude Desktop requires the local path to your cloned repository.

Add the following to your claude_desktop_config.json (replace the paths with your actual local paths):

"zim-mcp-server": {
  "command": "uv",
  "args": [
    "--directory",
    "path\\to\\zim-mcp-server",   // e.g., D:\\zim-mcp-server
    "run",
    "server.py",
    "path\\to\\zim\\files"      // e.g., D:\\ZIM
  ]
}
  • "path\\to\\zim-mcp-server": Local path to your cloned zim-mcp-server repository (e.g., D:\zim-mcp-server).
  • "path\\to\\zim\\files": Directory containing your ZIM files (e.g., D:\ZIM).

Claude Desktop will recognize the server only after this configuration.


Available Tools

list_zim_files - List all ZIM files in allowed directories

No parameters required.

search_zim_file - Search within ZIM file content

Required parameters:

  • zimFilePath (string): Path to the ZIM file
  • query (string): Search query term

Optional parameters:

  • limit (integer, default: 10): Maximum number of results to return
  • offset (integer, default: 0): Starting offset for results (for pagination)

get_zim_entry - Get detailed content of a specific entry in a ZIM file

Required parameters:

  • zimFilePath (string): Path to the ZIM file
  • entryPath (string): Entry path, e.g., 'A/Some_Article'

Optional parameters:

  • maxContentLength (integer, default: 100000): Maximum length of returned content

Examples

Listing ZIM files:

{
  "name": "list_zim_files"
}

Response:

{
  "Found 2 ZIM files in 1 directories:

  [
    {
      "name": "wikipedia_en_all_nopic_2023-07.zim",
      "path": "D:/ZIM/wikipedia_en_all_nopic_2023-07.zim",
      "directory": "D:/ZIM",
      "size": "95123.45 MB",
      "modified": "2023-08-01T12:00:00"
    },
    {
      "name": "wiktionary_en_all_nopic_2023-07.zim",
      "path": "D:/ZIM/wiktionary_en_all_nopic_2023-07.zim",
      "directory": "D:/ZIM",
      "size": "1234.56 MB",
      "modified": "2023-08-01T12:30:00"
    }
  ]
}

Searching ZIM files:

{
  "name": "search_zim_file",
  "arguments": {
    "zimFilePath": "D:/ZIM/wikipedia_en_all_nopic_2023-07.zim",
    "query": "artificial intelligence",
    "limit": 3
  }
}

Response:

Found 120 matches for "artificial intelligence", showing 1-3:

## 1. Artificial intelligence
Path: A/Artificial_intelligence
Snippet: Artificial intelligence (AI) is intelligence demonstrated by machines, as opposed to intelligence displayed by humans or by other animals. ...

## 2. History of artificial intelligence
Path: A/History_of_artificial_intelligence
Snippet: The history of artificial intelligence (AI) began in antiquity, with myths, stories and rumors of artificial beings endowed with intelligence or consciousness by master craftsmen. ...

## 3. Philosophy of artificial intelligence
Path: A/Philosophy_of_artificial_intelligence
Snippet: The philosophy of artificial intelligence is a branch of the philosophy of technology that explores artificial intelligence and its implications for knowledge, reality, consciousness, and the human mind. ...

Getting ZIM entries:

{
  "name": "get_zim_entry",
  "arguments": {
    "zimFilePath": "D:/ZIM/wikipedia_en_all_nopic_2023-07.zim",
    "entryPath": "A/Artificial_intelligence"
  }
}

Response:

# Artificial intelligence

Path: A/Artificial_intelligence
Type: text/html
## Content

Artificial intelligence (AI) is intelligence demonstrated by machines, as opposed to intelligence displayed by humans or by other animals. Examples of specific artificial intelligence applications include expert systems, natural language processing, and computer vision.

Leading AI textbooks define the field as the study of "intelligent agents": any system that perceives its environment and takes actions that maximize its chance of achieving its goals. Some popular accounts use the term "artificial intelligence" to describe machines that mimic "cognitive" functions that humans associate with the human mind, such as "learning" and "problem solving".

...

License

MIT

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

File details

Details for the file iflow_mcp_thinkinai_hackathon_zim_mcp_server-0.1.0.tar.gz.

File metadata

  • Download URL: iflow_mcp_thinkinai_hackathon_zim_mcp_server-0.1.0.tar.gz
  • Upload date:
  • Size: 8.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.10.0 {"installer":{"name":"uv","version":"0.10.0","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Debian GNU/Linux","version":"13","id":"trixie","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":null}

File hashes

Hashes for iflow_mcp_thinkinai_hackathon_zim_mcp_server-0.1.0.tar.gz
Algorithm Hash digest
SHA256 b3a8009927ca3b58d1ede1b130edec7f96feb946b143638b933b7ad81ca9dd08
MD5 923e2c3c0f4c72421d820d97a4e450f0
BLAKE2b-256 4866bb65289c9581bf04bdc699cbdb2cffcdfbd8f92b061c9037618fb8494c87

See more details on using hashes here.

File details

Details for the file iflow_mcp_thinkinai_hackathon_zim_mcp_server-0.1.0-py3-none-any.whl.

File metadata

  • Download URL: iflow_mcp_thinkinai_hackathon_zim_mcp_server-0.1.0-py3-none-any.whl
  • Upload date:
  • Size: 9.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.10.0 {"installer":{"name":"uv","version":"0.10.0","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Debian GNU/Linux","version":"13","id":"trixie","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":null}

File hashes

Hashes for iflow_mcp_thinkinai_hackathon_zim_mcp_server-0.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 eb38e18ae57202479b0d2557e32a665849213ef7f0a6a20b0b0087ca10cc7143
MD5 00d740f6da06379aa9fefa08517276a3
BLAKE2b-256 51b952e62c6765513d3481299b0f5b562ad984ff161f98156075a61ec344abd3

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page