Offline Wikipedia MCP Server 📚🔌

A fast, completely offline Model Context Protocol (MCP) server that connects local or cloud LLMs to locally downloaded Kiwix archives (.zim files).

This project bridges the gap between Large Language Models (running locally in LM Studio, Claude Desktop, or Cursor) and massive offline knowledge bases. By using the official Python MCP SDK and libzim, your LLM can search and read full Wikipedia articles — and any other Kiwix archive — without an internet connection.

✨ Features

• 🔍 Smart search — uses full-text index search with automatic fallback to title/prefix search
• 📚 Multi-archive support — point at a folder and every .zim file inside is loaded automatically
• 📄 Direct article lookup — retrieve a specific article by exact title, bypassing search
• 🏷️ Source labelling — results show which archive they came from (e.g. [wikipedia_en_wp1-0.8_nopic_2026-04])
• 🧹 Clean output — strips HTML, scripts, tables, citation numbers [1], and [edit] markers
• ✂️ Configurable truncation — prevent context-window overflows with WIKI_MAX_CHARS
• 🔒 Thread-safe — double-checked locking for safe use in concurrent MCP environments
• 📦 Any .zim file — works with Wikipedia, Wiktionary, Stack Overflow, and other Kiwix archives

🛠️ Tools Exposed to the LLM

Tool	Description
search_wikipedia(query, num_results)	Search all loaded archives using full-text index with fallback to title/prefix search
get_article(title)	Fetch a specific article by its exact title, searching across all loaded archives

📥 Step 1 — Download Kiwix .zim Archives

Because LLMs only process text, it is highly recommended to download "nopic" (no pictures) versions to save disk space.

1. Go to the Kiwix Library: https://library.kiwix.org/?lang=eng&q=wikipedia
2. Recommended files:
   • Wikipedia English (wp1/Mini, nopic) — most important articles, no images (~2 GB)
   • Wikipedia English (Maxi, nopic) — full Wikipedia, no images (~22 GB)
3. Save all .zim files into a single dedicated folder (e.g. ~/kiwix-zim/). The server will load every .zim file in that folder automatically.

⚠️ macOS users: Do not store your .zim files inside ~/Documents, ~/Desktop, or ~/Downloads. macOS restricts app access to those folders and will cause an Error opening ZIM file. Use your home directory or a custom folder instead (e.g. ~/kiwix-zim/).

🚀 Step 2 — Installation

git clone https://github.com/Rome-NotBeepBoop/mcp-offline-wikipedia.git
cd mcp-offline-wikipedia

# Create and activate a virtual environment
python -m venv venv
source venv/bin/activate        # Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

⚙️ Step 3 — Configure Your MCP Client

Replace the example paths below with your actual paths.

⚠️ Always use the full path to the venv Python (venv/bin/python), not the system python3. This guarantees the correct libzim version is used.

Claude Desktop

Edit ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):

{
  "mcpServers": {
    "offline-wikipedia": {
      "command": "/absolute/path/to/mcp-offline-wikipedia/venv/bin/python",
      "args": ["/absolute/path/to/mcp-offline-wikipedia/mcp_wiki_server.py"],
      "env": {
        "WIKI_ZIM_DIR": "/absolute/path/to/your/kiwix-zim/",
        "WIKI_MAX_CHARS": "15000"
      }
    }
  }
}

Cursor

Add the following to your Cursor MCP config (.cursor/mcp.json):

{
  "mcpServers": {
    "offline-wikipedia": {
      "command": "/absolute/path/to/mcp-offline-wikipedia/venv/bin/python",
      "args": ["/absolute/path/to/mcp-offline-wikipedia/mcp_wiki_server.py"],
      "env": {
        "WIKI_ZIM_DIR": "/absolute/path/to/your/kiwix-zim/"
      }
    }
  }
}

LM Studio

In LM Studio, go to Developer → mcp.json and fill in:

{
  "mcpServers": {
    "offline-wikipedia": {
      "command": "/absolute/path/to/mcp-offline-wikipedia/venv/bin/python",
      "args": ["/absolute/path/to/mcp-offline-wikipedia/mcp_wiki_server.py"],
      "env": {
        "WIKI_ZIM_DIR": "/absolute/path/to/your/kiwix-zim/",
        "WIKI_MAX_CHARS": "15000"
      }
    }
  }
}

🌍 Environment Variables

Variable	Required	Default	Description
WIKI_ZIM_DIR	✅ Preferred	—	Path to a folder — every .zim file inside is loaded
WIKI_ZIM_PATH	Legacy	—	Path to a single .zim file (use WIKI_ZIM_DIR instead)
WIKI_MAX_CHARS	No	15000	Max characters returned per article

WIKI_ZIM_DIR takes priority over WIKI_ZIM_PATH if both are set.

❓ Troubleshooting

Neither WIKI_ZIM_DIR nor WIKI_ZIM_PATH is set → Make sure the env block is present in your MCP client config with the correct variable name.

ZIM archive not found at: ... → Double-check the path. On Windows, use forward slashes or escaped backslashes: C:/Users/you/kiwix-zim/.

macOS: Error opening ZIM file even though the file exists and the path is correct → macOS restricts app access to ~/Documents, ~/Desktop, and ~/Downloads without explicit permission. LM Studio (and the Python process it spawns) may be silently blocked. Two fixes:

• Quick fix: Move your .zim files to ~/kiwix-zim/ or any other folder you created yourself, and update WIKI_ZIM_DIR accordingly.
• Proper fix: Go to System Settings → Privacy & Security → Files and Folders and grant LM Studio access to the folder containing your .zim files.

Error opening ZIM file — but the file opens fine in a Python terminal → LM Studio is using a different Python than your terminal. Always use the venv Python in your MCP config (venv/bin/python), not the system python3. Verify it has the right libzim:

/absolute/path/to/venv/bin/python -c "import libzim; print('ok')"

Server starts but the LLM says it can't find any articles → Some .zim files don't have a full-text index. The server will automatically fall back to title search, but results may be less accurate for vague queries. Try using the exact article title.

High memory usage → Each .zim archive is loaded on first use. Larger archives (Maxi) will use more RAM. The Mini/nopic version is recommended for most use cases.

🤝 Contributing

Contributions are welcome! Please open an issue first to discuss what you'd like to change. Pull requests should target the main branch.

1. Fork the repo
2. Create a feature branch (git checkout -b feature/my-improvement)
3. Commit your changes (git commit -m 'Add some improvement')
4. Push to your branch (git push origin feature/my-improvement)
5. Open a Pull Request

📜 License

This project is licensed under the MIT License — see the LICENSE file for details.