What tools does kagi-server implement?
Only `kagi_search` is currently implemented. `kagi_summarize`, `kagi_fastgpt`, and `kagi_enrich` are planned but not yet available.
@ac3xx
Basic information
A Model Context Protocol server implementation for Kagi's API
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"mcp-servers-kagi": {
"command": "npx",
"args": [
"@smithery/cli",
"install",
"kagi-server",
"--client",
"claude"
]
}
}
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
Fetch the live tool list by running this server in a temporary sandbox using the button above.
A TypeScript-based MCP server that integrates the Kagi Search API, providing tools for web search operations. It is designed for use with AI assistants like Claude Desktop.
Install dependencies with npm install, build with npm run build, set the KAGI_API_KEY environment variable in a .env file, and add the server configuration to Claude Desktop's config file (e.g., claude_desktop_config.json). Alternatively, install via Smithery using npx @smithery/cli install kagi-server --client claude.
kagi_search tool for web searches via Kagi APIOnly `kagi_search` is currently implemented. `kagi_summarize`, `kagi_fastgpt`, and `kagi_enrich` are planned but not yet available.
Create a `.env` file in the project root with `KAGI_API_KEY=your_api_key_here`. The Kagi API is currently in private beta.
Use the MCP Inspector by running `npm run inspector`, which provides a URL for debugging tools in a browser.
Install via Smithery (`npx @smithery/cli install kagi-server --client claude`) or manually by adding the server config to `claude_desktop_config.json` with the path to `build/index.js` and the `KAGI_API_KEY` environment variable.
The server communicates over stdio using the Model Context Protocol.

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