Kagi
Enables integration with Kagi search engine services including web search, content summarization from URLs, and AI assistant conversations. Uses session tokens to access Kagi's search API, summarizer, and AI models directly within MCP-compatible appl
What is Kagi?
Kagi is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to enables integration with kagi search engine services including web search, content summarization from urls, and ai assistant conversations. uses session tokens to access kagi's search api, summarizer,...
Enables integration with Kagi search engine services including web search, content summarization from URLs, and AI assistant conversations. Uses session tokens to access Kagi's search API, summarizer, and AI models directly within MCP-compatible appl
This server falls under the Search & Data Extraction category on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- Enables integration with Kagi search engine services includi
Use Cases
Maintainer
Works with
Installation
Manual Installation
npx kagi-mcp-serverConfiguration
Configuration Details
claude_desktop_config.json
Performance
Response Metrics
Resource Usage
How to Set Up and Use Kagi
The Kagi MCP server (kagimcp) is the official integration between Kagi's privacy-focused search engine and MCP-compatible AI clients. It exposes two powerful tools: kagi_search_fetch for searching the web, news, videos, podcasts, and images with optional full-page content extraction and Kagi lenses, and kagi_extract for fetching any URL's full content as clean markdown. A Kagi API key is required, enabling teams to bring high-quality, ad-free search results and content extraction directly into Claude conversations.
Prerequisites
- A Kagi account with an active API key (obtain at https://kagi.com/settings?p=api)
- Python 3.10 or later with uv installed (https://docs.astral.sh/uv/)
- An MCP-compatible client such as Claude Desktop or Claude Code
Obtain a Kagi API key
Log in to your Kagi account, go to Settings → API, and generate an API key. Note that API usage is billed separately from your Kagi subscription.
Add the server to Claude Code (quickest method)
Run this single command to register the Kagi MCP server in Claude Code, injecting your API key as an environment variable.
claude mcp add kagi -e KAGI_API_KEY="YOUR_API_KEY_HERE" -- uvx kagimcpConfigure Claude Desktop
Add the server entry to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS). Replace YOUR_API_KEY_HERE with your actual key.
{
"mcpServers": {
"kagi": {
"command": "uvx",
"args": ["kagimcp"],
"env": {
"KAGI_API_KEY": "YOUR_API_KEY_HERE",
"FASTMCP_LOG_LEVEL": "ERROR"
}
}
}
}Optional: tune timeout and retry settings
Add environment variables to adjust search and extraction timeouts or disable retries for faster failure feedback in automated pipelines.
{
"mcpServers": {
"kagi": {
"command": "uvx",
"args": ["kagimcp"],
"env": {
"KAGI_API_KEY": "YOUR_API_KEY_HERE",
"KAGI_SEARCH_TIMEOUT": "15",
"KAGI_EXTRACT_TIMEOUT": "45",
"KAGI_MAX_RETRIES": "1"
}
}
}
}Restart Claude Desktop and verify
Quit and reopen Claude Desktop. The hammer icon in the toolbar should appear, and asking Claude to search the web should trigger the kagi_search_fetch tool.
Kagi Examples
Client configuration
Production-ready Claude Desktop config for the Kagi MCP server with logging suppressed.
{
"mcpServers": {
"kagi": {
"command": "uvx",
"args": ["kagimcp"],
"env": {
"KAGI_API_KEY": "YOUR_API_KEY_HERE",
"FASTMCP_LOG_LEVEL": "ERROR",
"KAGI_SEARCH_TIMEOUT": "10",
"KAGI_EXTRACT_TIMEOUT": "30",
"KAGI_MAX_RETRIES": "2"
}
}
}
}Prompts to try
Sample prompts that exercise both kagi_search_fetch and kagi_extract.
- "Search Kagi for the latest news about the Model Context Protocol"
- "Who was Time's 2024 Person of the Year? Search Kagi for the answer."
- "Extract the full content of https://en.wikipedia.org/wiki/Model_Context_Protocol and summarise it"
- "Search for recent Python 3.13 release notes and extract the changelog page"
- "Find the top 5 results for 'best open-source LLM 2025' using Kagi"Troubleshooting Kagi
AuthenticationError or 401 response from Kagi API
Double-check that KAGI_API_KEY is set correctly in the env block of your config. Kagi API keys are separate from your login password — generate one at https://kagi.com/settings?p=api.
Search returns no results or times out
Increase KAGI_SEARCH_TIMEOUT (default 10 seconds) to 20 or 30. Also verify your Kagi account has available API credits — usage is metered per search call.
uvx kagimcp fails with 'package not found'
Ensure uv is installed and up to date ('uv --version' should be 0.4+). The package name on PyPI is 'kagimcp'. Run 'uvx kagimcp --version' manually to test before adding it to the config.
Frequently Asked Questions about Kagi
What is Kagi?
Kagi is a Model Context Protocol (MCP) server that enables integration with kagi search engine services including web search, content summarization from urls, and ai assistant conversations. uses session tokens to access kagi's search api, summarizer, and ai models directly within mcp-compatible appl It connects AI assistants to external tools and data sources through a standardized interface.
How do I install Kagi?
Follow the installation instructions on the Kagi GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.
Which AI clients work with Kagi?
Kagi works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is Kagi free to use?
Yes, Kagi is open source and available under the MIT License license. You can use it freely in both personal and commercial projects.
Kagi Alternatives — Similar Search & Data Extraction Servers
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Xiaohongshu
★ 13.7kMCP for xiaohongshu.com
Browse More Search & Data Extraction MCP Servers
Explore all search & data extraction servers available in the MCPgee directory. Each server includes setup guides for Claude, Cursor, and VS Code.
Set Up Kagi in Your Editor
Choose your AI client for step-by-step setup instructions.
Quick Config Preview
Add this to your claude_desktop_config.json or .cursor/mcp.json
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