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MCP Server

Kagi MCP Server

Allows the use of Kagi's API for web searching and content enrichment through methods like fastgpt, enrich/web, and enrich/news.

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GitHub Stars
11/22/2025
Last Updated
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Please check the documentation below.
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README Documentation

Kagi MCP server

smithery badge MCP server that allows to search web using Kagi API

Kagi Server MCP server

Components

Resources

The server implements calls of API methods:

  • fastgpt
  • enrich/web
  • enrich/news

Prompts

The server provides doesn't provide any prompts:

Tools

The server implements several tools:

  • ask_fastgpt to search web and find an answer
  • enrich_web to enrich model context with web content
  • enrich_news to enrich model context with latest news

Configuration

Quickstart

Install

Installing via Smithery

To install the Kagi MCP server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install kagi-mcp --client claude

Claude Desktop

On MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json

Development/Unpublished Servers Configuration ``` "mcpServers": { "kagi-mcp": { "command": "uv", "args": [ "--directory", "path_to_project", "run", "kagi-mcp" ], "env": { "KAGI_API_KEY": "YOUR API KEY" } } } ```

Development

Building and Publishing

To prepare the package for distribution:

  1. Sync dependencies and update lockfile:
uv sync
  1. Build package distributions:
uv build

This will create source and wheel distributions in the dist/ directory.

  1. Publish to PyPI:
uv publish

Note: You'll need to set PyPI credentials via environment variables or command flags:

  • Token: --token or UV_PUBLISH_TOKEN
  • Or username/password: --username/UV_PUBLISH_USERNAME and --password/UV_PUBLISH_PASSWORD

Debugging

npx @modelcontextprotocol/inspector uv --directory path_to_project run kagi-mcp

Quick Actions

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Key Features

Model Context Protocol
Secure Communication
Real-time Updates
Open Source

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