kagi-ken-mcp

Node.js MCP server providing Kagi search, summarization and AI assistant tools using your existing Kagi session token.

Features

• Search: Kagi web search with multiple query support
• Summarizer: URL/content summarization with customizable formats
• Assistant: AI-powered conversations using Kagi's AI models

Environment Variables

The server requires different environment variables depending on which features you want to use:

For Search and Summarization only:

• KAGI_SESSION_TOKEN: Your Kagi session token
• KAGI_SUMMARIZER_ENGINE: Summarizer engine to use (optional, default: "default")

For Assistant feature (in addition to the above):

• KAGI_SEARCH_COOKIE: Your _kagi_search_ cookie value
• KAGI_MODEL_LIST: Comma-separated list of available AI models (required for assistant)
• KAGI_DEFAULT_MODEL: Default model to use (optional, uses first from list if not specified)

Setup

Get Required Tokens

Session Token

1. Visit Kagi Settings
2. Copy the Session Link
3. Extract the token value
4. Set KAGI_SESSION_TOKEN env variable

Search Cookie (for Assistant feature)

1. Open browser developer tools (F12)
2. Go to Kagi.com and login
3. In Application/Storage tab, find Cookies for kagi.com
4. Copy the value of _kagi_search_ cookie
5. Set KAGI_SEARCH_COOKIE env variable

Model Configuration (for Assistant feature)

• Set KAGI_MODEL_LIST with comma-separated available models (e.g., "o3-pro,claude-4-sonnet,gemini-2-5-pro")
• Optionally set KAGI_DEFAULT_MODEL to specify default model

Claude Desktop

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "kagi-mcp": {
      "command": "npx",
      "args": ["-y", "@z23cc/kagi-mcp"],
      "env": {
        "KAGI_SESSION_TOKEN": "YOUR_SESSION_TOKEN_HERE",
        "KAGI_SEARCH_COOKIE": "YOUR_KAGI_SEARCH_COOKIE_HERE",
        "KAGI_MODEL_LIST": "o3-pro,claude-4-sonnet,gemini-2-5-pro",
        "KAGI_DEFAULT_MODEL": "claude-4-sonnet",
        "KAGI_SUMMARIZER_ENGINE": "default"
      }
    }
  }
}

Post-install

Disable Claude Desktop's built-in websearch so it'll use this here MCP server. And maybe add this to your "Personal preferences" (i.e., system prompt) in Settings:

For web searches, use kagi-ken-mcp MCP server's `kagi_search_fetch` tool.
For summarizing a URL, use the kagi-ken-mcp MCP server's `kagi_summarizer` tool.
For AI conversations, use the kagi-ken-mcp MCP server's `kagi_assistant` tool.

Claude Code

Add MCP server to Claude Code:

claude mcp add kagi-mcp \
  --scope user \
  --env KAGI_SESSION_TOKEN="YOUR_SESSION_TOKEN_HERE" \
  --env KAGI_SEARCH_COOKIE="YOUR_KAGI_SEARCH_COOKIE_HERE" \
  --env KAGI_MODEL_LIST="o3-pro,claude-4-sonnet,gemini-2-5-pro" \
  --env KAGI_DEFAULT_MODEL="claude-4-sonnet" \
  npx -y @z23cc/kagi-mcp

Post-install

Disable Claude Code's built-in web search (optional) by setting the permission in the relevant .claude/settings*.json file:

{
  "permissions": {
    "deny": [
      "WebSearch"
    ],
    "allow": [
      "mcp__kagi-mcp__kagi_search_fetch",
      "mcp__kagi-mcp__kagi_summarizer",
      "mcp__kagi-mcp__kagi_assistant"
    ]
  }
}

Usage: Pose query that requires use of a tool

e.g. "Who was time's 2024 person of the year?" for search, or "summarize this video: https://www.youtube.com/watch?v=sczwaYyaevY" for summarizer.

Tools

kagi_search_fetch

Fetch web results based on one or more queries using the Kagi Search API. Results are numbered continuously for easy reference.

Parameters:

• queries (array of strings): One or more search queries

kagi_summarizer

Summarize content from URLs using the Kagi Summarizer API. Supports various document types including webpages, videos, and audio.

Parameters:

• url (string): URL to summarize
• summary_type (enum): "summary" for paragraph prose or "takeaway" for bullet points (default: "summary")
• target_language (string, optional): Language code (e.g., "EN" for English, default: "EN")

kagi_assistant

Interact with Kagi's AI assistant models for conversations and queries.

Parameters:

• message (string): The message or question to send to the assistant
• model (string, optional): AI model to use (default: uses configured default model)
• web_search (boolean, optional): Enable web search integration (default: true)
• image (string, optional): Base64 encoded image for vision models

Development

Project Structure

kagi-ken-mcp/
├── src/
│   ├── index.js              # Main server entry point
│   ├── tools/
│   │   ├── search.js         # Search tool implementation
│   │   ├── summarizer.js     # Summarizer tool implementation
│   │   └── assistant.js      # Assistant tool implementation
│   └── utils/
│       └── formatting.js     # Utility functions
├── package.json
└── README.md

Installation

1. Clone the repository:

   git clone https://github.com/z23cc/kagi-mcp.git
   cd kagi-mcp

2. Install dependencies:

   npm install

Running in Development Mode

npm run dev

Debugging

Use the MCP Inspector to debug:

npx @modelcontextprotocol/inspector node ./src/index.js

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Test with the MCP Inspector
5. Submit a pull request

Related Projects

• czottmann/kagi-ken - Unofficial session token-based Kagi client, Node
• czottmann/kagi-ken-cli - Unofficial Node session token-based CLI tool, Node
• Official Kagi MCP Server - Python
• Model Context Protocol