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Kagi-server MCP Server: Developer-Friendly, Scalable AI Workflows - MCP Implementation

Kagi-server MCP Server: Developer-Friendly, Scalable AI Workflows

Kagi-server MCP Server: A developer-friendly Model Context Protocol implementation for Kagi's API, enabling seamless AI workflows with scalable, enterprise-grade reliability.

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About Kagi-server MCP Server

What is Kagi-server MCP Server: Developer-Friendly, Scalable AI Workflows?

Kagi-server is a TypeScript-based Model Context Protocol (MCP) server designed to integrate the Kagi Search API into AI workflows. It provides developers with a structured framework to build scalable applications leveraging Kagi's advanced search capabilities. Currently in private testing, this server simplifies the process of embedding contextual search operations within custom tools and automation pipelines.

How to Use Kagi-server MCP Server

To begin, developers must install dependencies using standard npm commands. Environment configuration requires setting API keys via environment variables and adjusting project settings for production use. Integration with platforms like Claude Desktop involves precise configuration steps outlined in documentation. Debugging workflows are supported through tools like the MCP Inspector, ensuring seamless error resolution during development.

Kagi-server MCP Server Features

Key Features of Kagi-server

  • Production-ready search tooling with Kagi API integration
  • Automatic TypeScript compilation and hot-reloading for rapid iteration
  • Support for upcoming features including content summarization and real-time response generation
  • Extensive logging and debugging capabilities through MCP Inspector

Use Cases for Developers

Teams leverage this server to:

  • Create custom search interfaces with contextual understanding
  • Automate content discovery processes for AI training datasets
  • Build intelligent agents that combine search with generative capabilities
  • Prototype scalable workflows for news aggregation and analysis

Kagi-server MCP Server FAQ

FAQ: Getting Started

Q: How do I install the server?
Follow the official guide to set up Node.js dependencies and configure API access. See Smithery documentation for advanced setup options.

Q: What's the roadmap for new features?
Planned enhancements include summarization tools (Q3 2024), real-time API endpoints, and multi-language support. Check GitHub issues for milestone updates.

Q: Can I contribute?
Yes! Contributions are welcome through PRs for documentation improvements, test cases, and core functionality enhancements. Join our Discord for developer discussions.

Content

kagi-server MCP Server

smithery badge MCP server for Kagi API integration

This is a TypeScript-based MCP server that integrates the Kagi Search API. It demonstrates core MCP concepts by providing:

  • Tools for performing web searches and other operations using Kagi's API (currently in private beta)

Features

Implemented Tools

  • kagi_search - Perform web searches using Kagi
    • Takes a query string and optional limit as parameters
    • Returns search results from Kagi's API

Planned Tools (Not Yet Implemented)

  • kagi_summarize - Generate summaries of web pages or text
  • kagi_fastgpt - Get quick responses using Kagi's FastGPT
  • kagi_enrich - Fetch enriched news results on specific topics

Development

Install dependencies:

npm install

Build the server:

npm run build

For development with auto-rebuild:

npm run watch

Environment Setup

Create a .env file in the root directory with your Kagi API key:

KAGI_API_KEY=your_api_key_here

Make sure to add .env to your .gitignore file to keep your API key secure.

Installation

Installing via Smithery

To install Kagi Server for Claude Desktop automatically via Smithery:

npx @smithery/cli install kagi-server --client claude

To use with Claude Desktop, add the server config:

On MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json On Windows: %APPDATA%/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "kagi-server": {
      "command": "/path/to/kagi-server/build/index.js",
      "env": {
        "KAGI_API_KEY": "your_api_key_here"
      }
    }
  }
}

Debugging

Since MCP servers communicate over stdio, debugging can be challenging. We recommend using the MCP Inspector, which is available as a package script:

npm run inspector

The Inspector will provide a URL to access debugging tools in your browser.

Usage

Once the server is running and connected to Claude Desktop, you can use it to perform web searches. For example:

  1. Ask Claude: "Can you search for information about the latest advancements in quantum computing?"
  2. Claude will use the kagi_search tool to fetch results from Kagi's API.
  3. Claude will then summarize or analyze the search results for you.

Note: The planned tools (summarize, fastgpt, enrich) are not yet implemented and cannot be used.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request. Some areas for contribution include:

  • Implementing the planned tools (summarize, fastgpt, enrich)
  • Improving error handling and input validation
  • Enhancing documentation and usage examples

License

This project is licensed under the MIT License.

Roadmap

  • Implement kagi_summarize tool for webpage and text summarization
  • Implement kagi_fastgpt tool for quick responses
  • Implement kagi_enrich tool for fetching enriched news results
  • Improve error handling and add more robust input validation
  • Add more comprehensive usage examples and documentation
  • Publish the package to npm for easy installation and use with Claude Desktop and npx

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