Kagi MCP server is a TypeScript-based Model-Context-Protocol (MCP) server that integrates the Kagi Search API. It provides tools for performing web searches and other operations using Kagi's API, currently in private beta. The server supports features like kagi_search for fetching search results and has planned tools such as kagi_summarize, kagi_fastgpt, and kagi_enrich which are not yet implemented.
The Kagi MCP server allows developers to leverage Kagi's powerful search capabilities within applications like Claude Desktop. By providing an interface for web searches, it enables users to retrieve information efficiently while offering potential future functionalities such as summarization, quick GPT responses, and enriched news data through additional tools.
Developers who want to integrate advanced search functionality into their projects or applications (like Claude Desktop) can benefit from this server. Additionally, contributors interested in improving open-source software may find opportunities to enhance the project by implementing new features, improving error handling, or expanding documentation.
You can install Kagi MCP server via Smithery for integration with Claude Desktop. On MacOS, the configuration file is located at ~/Library/Application Support/Claude/claude_desktop_config.json, and on Windows, it’s found at %APPDATA%/Claude/claude_desktop_config.json. The server requires proper setup of environment variables including your Kagi API key.
You should use Kagi MCP server when you need to perform web searches programmatically using Kagi's API or plan to utilize its upcoming features like text summarization, fast GPT responses, or enriched news data. It’s ideal during development phases where external search integrations enhance application capabilities.
Create a .env file in the root directory containing your Kagi API key (e.g., KAGI_API_KEY=your_api_key_here). Ensure that .env is added to your .gitignore file to secure your API key. Then, install dependencies using npm install, build the server with npm run build, and start it with appropriate commands depending on your platform.
Yes, debugging is facilitated by the MCP Inspector tool. Run npm run inspector to get a URL that opens debugging tools in your browser. This helps monitor communication between the server and client over stdio effectively.
Future plans include implementing the kagi_summarize tool for webpage/text summarization, kagi_fastgpt for quick responses, and kagi_enrich for fetching enriched news results. Improvements in error handling, input validation, comprehensive usage examples, and publishing the package to npm are also part of the roadmap.
Yes, Kagi MCP server is open-source and licensed under the MIT License. Contributions are welcome, especially in areas like implementing planned tools, enhancing error handling, and improving documentation.
MCP (Model Context Protocol) is an open protocol designed to standardize how applications provide context information to large language models (LLMs). Like a 'USB-C port' for AI applications, MCP ensures AI models can seamlessly connect with various data sources and tools.
An MCP Server is a server that supports the MCP protocol, enabling the exchange of contextual information between applications and AI models in a standardized way. It provides developers with an easy way to integrate AI models with databases, APIs, or other data sources.
An MCP Server eliminates the complexity of developing custom adapters by unifying the connection between AI models and various data sources. Whether you're a developer, data scientist, or AI app builder, an MCP Server simplifies the integration process, saving time and resources.
An MCP Server acts as an intermediary bridge, converting contextual information from various data sources into a format that AI models can understand. By adhering to the MCP protocol, it ensures data is transmitted between applications and AI models in a standardized manner.
At mcpserver.shop, you can browse our MCP Server Directory. The directory is categorized by industry (e.g., finance, healthcare, education), and each server comes with detailed descriptions and tags to help you quickly find the option that suits your needs.
The MCP Server Directory on mcpserver.shop is free to browse. However, some servers are hosted by third-party providers and may involve usage fees. Check the detailed page of each server for specific information.
MCP Servers support a wide range of data sources, including databases, APIs, cloud services, and custom tools. The flexibility of the MCP protocol allows it to connect almost any type of data source to AI models.
MCP Servers are primarily designed for developers, data scientists, and AI app builders. However, mcpserver.shop provides detailed documentation and guides to help users of varying technical levels get started easily.
Yes, MCP is an open-source protocol that encourages community participation and collaboration. For more details or to contribute, visit the official MCP documentation.
On mcpserver.shop, each MCP Server’s detailed page includes the provider’s contact information or a link. You can directly reach out to the provider for more details or technical support.