Kagi MCP server
Servidor MCP kagi-server
Servidor MCP para la integración de la API de Kagi
Este es un servidor MCP basado en TypeScript que integra la API de búsqueda de Kagi. Demuestra los conceptos básicos de MCP al proporcionar:
Herramientas para realizar búsquedas web y otras operaciones utilizando la API de Kagi (actualmente en versión beta privada)
Características
Herramientas implementadas
kagi_search- Realiza búsquedas web usando KagiToma una cadena de consulta y un límite opcional como parámetros
Devuelve resultados de búsqueda de la API de Kagi
Herramientas planificadas (aún no implementadas)
kagi_summarize- Genera resúmenes de páginas web o textokagi_fastgpt: obtenga respuestas rápidas utilizando FastGPT de Kagikagi_enrich- Obtener resultados de noticias enriquecidos sobre temas específicos
Related MCP server: Kagi MCP Server
Desarrollo
Instalar dependencias:
npm installConstruir el servidor:
npm run buildPara desarrollo con reconstrucción automática:
npm run watchConfiguración del entorno
Cree un archivo .env en el directorio raíz con su clave API de Kagi:
KAGI_API_KEY=your_api_key_hereAsegúrese de agregar .env a su archivo .gitignore para mantener su clave API segura.
Instalación
Instalación mediante herrería
Para instalar Kagi Server para Claude Desktop automáticamente a través de Smithery :
npx @smithery/cli install kagi-server --client claudePara utilizar con Claude Desktop, agregue la configuración del servidor:
En MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json En 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"
}
}
}
}Depuración
Dado que los servidores MCP se comunican a través de stdio, la depuración puede ser complicada. Recomendamos usar el Inspector MCP , disponible como script de paquete:
npm run inspectorEl Inspector proporcionará una URL para acceder a las herramientas de depuración en su navegador.
Uso
Una vez que el servidor esté en funcionamiento y conectado a Claude Desktop, podrá usarlo para realizar búsquedas web. Por ejemplo:
Pregúntale a Claude: "¿Puedes buscar información sobre los últimos avances en computación cuántica?"
Claude utilizará la herramienta
kagi_searchpara obtener resultados de la API de Kagi.Luego, Claude resumirá o analizará los resultados de la búsqueda para usted.
Nota: Las herramientas planificadas (resumir, fastgpt, enriquecer) aún no están implementadas y no se pueden utilizar.
Contribuyendo
¡Agradecemos sus contribuciones! No dude en enviar una solicitud de incorporación de cambios. Algunas áreas de contribución incluyen:
Implementar las herramientas planificadas (resumir, fastgpt, enriquecer)
Mejorar el manejo de errores y la validación de entradas
Mejorar la documentación y los ejemplos de uso
Licencia
Este proyecto está licenciado bajo la licencia MIT.
Hoja de ruta
Implementar la herramienta
kagi_summarizepara el resumen de páginas web y textoImplementar la herramienta
kagi_fastgptpara obtener respuestas rápidasImplementar la herramienta
kagi_enrichpara obtener resultados de noticias enriquecidosMejorar el manejo de errores y agregar una validación de entrada más robusta
Agregue ejemplos de uso y documentación más completos
Publique el paquete en npm para facilitar su instalación y uso con Claude Desktop y npx
Available Tools
1 toolkagi_searchC
Perform web search using Kagi
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| query | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions 'Perform web search' which implies read-only behavior, but doesn't disclose any behavioral traits like rate limits, authentication needs, response format, or potential side effects. This leaves significant gaps for a tool with external dependencies.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise—a single sentence with zero waste. It's front-loaded with the core purpose and efficiently communicates the essential function without unnecessary details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and low schema description coverage, the description is incomplete. It doesn't address behavioral aspects, parameter usage, or result expectations, making it inadequate for a tool that interacts with an external web search service.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It adds no meaning beyond the schema—doesn't explain what 'query' should contain, how 'limit' affects results, or any parameter nuances. The schema defines types and constraints, but the description offers no semantic context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Perform web search') and the resource/service ('using Kagi'), which is specific and unambiguous. However, with no sibling tools mentioned, it cannot demonstrate differentiation from alternatives, so it doesn't reach the highest score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, prerequisites, or any contextual limitations. It simply states what the tool does without offering usage instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
1 tool update
v1.0.0- First observed
kagi_search
TDQS
Scored across 1 tool
With only one tool, there is no possibility of ambiguity or overlap between tools. The tool's purpose is clearly defined as performing web searches using Kagi, leaving no room for misselection.
A single tool inherently has perfect naming consistency, as there are no other tools to compare it against. The name 'kagi_search' follows a clear verb_noun pattern, but consistency cannot be assessed across a set of one.
A single tool is too few for a server that appears to be focused on web search functionality, as it lacks complementary operations like summarization, filtering, or handling search results. This minimal scope feels incomplete for the domain.
The tool surface is severely incomplete for a web search domain, as it only provides raw search capability without tools for processing, refining, or managing search results. This creates significant gaps that will limit agent effectiveness.
Maintenance
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