Kibana MCP Server
Servidor Kibana MCP
Especificación API
Este proyecto se basa en la documentación oficial de la API de Elastic Kibana y utiliza la especificación OpenAPI YAML de Elastic Stack 8.x (ES8) para recuperar y gestionar dinámicamente todos los endpoints de la API de Kibana. Para obtener la información más reciente, consulte la documentación de la API de Kibana .
Una implementación de servidor Kibana MCP que permite que cualquier cliente compatible con MCP (como Claude Desktop) acceda a su instancia de Kibana a través de lenguaje natural o solicitudes programáticas.
Este proyecto es mantenido por la comunidad y no es un producto oficial de Elastic o MCP.
Características
Conectarse a instancias locales o remotas de Kibana
Autenticación segura (nombre de usuario/contraseña)
Compatibilidad con certificados SSL/TLS y CA personalizados
Expone los puntos finales de la API de Kibana como herramientas y recursos
Busque, visualice y ejecute API de Kibana desde clientes MCP
Seguro de tipos, extensible y fácil de integrar
Related MCP server: mshegolev/kibana-mcp
Estructura del directorio
├── index.ts # Server entry point
├── src/
│ ├── types.ts # Type definitions and schemas
│ ├── base-tools.ts # Tool registration and API logic
│ ├── prompts.ts # Prompt registration (expert & resource helper)
│ └── resources.ts # Resource registration (API paths/URIs)
├── kibana-openapi-source.yaml # Kibana API OpenAPI index
├── README.md # English documentation
├── README_zh.md # Chinese documentationRecursos
URI del recurso | Descripción |
| Devuelve todos los puntos finales de API de Kibana disponibles (se pueden filtrar con el parámetro |
| Devuelve detalles para un punto final de API específico |
Ejemplos:
kibana-api://paths?search=saved_objectskibana-api://path/GET/%2Fapi%2Fstatus
Herramientas
Nombre de la herramienta | Descripción | Parámetros de entrada |
| Obtenga el estado actual del servidor Kibana | Ninguno |
| Ejecutar una solicitud de API de Kibana personalizada |
|
| Buscar puntos finales de la API de Kibana por palabra clave |
|
| Listar todos los puntos finales de la API de Kibana | Ninguno |
| Obtener detalles de un punto final de API de Kibana específico |
|
Indicaciones
Nombre del aviso | Descripción |
| El modo experto de herramientas (muy recomendado en Claude Desktop) permite el análisis inteligente, la búsqueda, la ejecución y la explicación de las API de Kibana mediante herramientas. Recomendado para la mayoría de los usuarios. |
| El modo de ayuda de recursos guía el acceso y uso de la información de la API de Kibana mediante las URI de recursos. Ideal para clientes que solo admiten el acceso a recursos o necesitan metadatos de la API sin procesar. |
Configuración
Configurar el servidor a través de variables de entorno:
Nombre de la variable | Descripción | Requerido |
| Dirección del servidor Kibana (por ejemplo , http://localhost:5601 ) | Sí |
| Nombre de usuario de Kibana | Sí |
| Contraseña de Kibana | Sí |
| Ruta del certificado CA (opcional, para verificación SSL) | No |
| Tiempo de espera de solicitud en ms (predeterminado 30000) | No |
| Máximo de reintentos de solicitud (predeterminado: 3) | No |
| Establezca en | No |
Uso
Iniciar el servidor
KIBANA_URL=http://your-kibana-server:5601 \
KIBANA_USERNAME=your-username \
KIBANA_PASSWORD=your-password \
NODE_TLS_REJECT_UNAUTHORIZED=0 \
npm startEjemplo de configuración de cliente MCP
Agregue al archivo de configuración de Claude Desktop (ruta de MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json ):
{
"mcpServers": {
"kibana-mcp-server": {
"command": "node",
"args": ["/path/to/mcp-server-kibana/dist/index.js"],
"env": {
"KIBANA_URL": "http://your-kibana-server:5601",
"KIBANA_USERNAME": "your-username",
"KIBANA_PASSWORD": "your-password",
"NODE_TLS_REJECT_UNAUTHORIZED": "0"
}
}
}
}Consultas de ejemplo
"¿Cuál es el estado de mi servidor Kibana?"
"Enumere todos los puntos finales de la API de Kibana disponibles".
"Mostrar detalles del punto final POST /api/saved_objects/_find".
"Ejecutar una solicitud de API personalizada para /api/status."
"Obtenga una lista de todos los paneles en Kibana".
"Consultar puntos finales de API relacionados con eventos de puntos finales".
"Enumere todos los puntos finales de API relacionados con el caso".
"Crear un nuevo caso en Kibana."
"Crear un nuevo panel en Kibana".
Dos modos de aviso en Claude Desktop
Al utilizar este servidor con Claude Desktop, se admiten dos modos de interacción de solicitud diferentes:
1. Modo de aviso basado en herramientas
Cómo funciona: Claude Desktop puede llamar directamente a las herramientas del servidor (como
get_status,execute_api,search_kibana_api_paths, etc.) para responder sus preguntas o realizar acciones.Ideal para: Usuarios que buscan una experiencia conversacional y guiada. El servidor buscará, ejecutará y explicará automáticamente las API de Kibana.
Ejemplo: "Mostrar todos los puntos finales de la API de Kibana relacionados con los objetos guardados".
Consejo de prueba: seleccione el indicador
kibana-tool-experten Claude Desktop para realizar pruebas de integración y luego comience a usarlo.
2. Modo de solicitud basado en recursos
Cómo funciona: Claude Desktop interactúa con el servidor a través de URI de recursos (como
kibana-api://pathsokibana-api://path/GET/%2Fapi%2Fstatus) y el servidor devuelve datos estructurados para que Claude los analice.Ideal para: usuarios avanzados, clientes MCP que solo admiten acceso a recursos o escenarios de programación que necesitan metadatos de API sin procesar.
Ejemplo: "Obtener el recurso kibana-api://paths?search=dashboard"
Nota: Los dos puntos finales en resources ( kibana-api://paths y kibana-api://path/{method}/{encoded_path} ) cuentan con sus herramientas base correspondientes ( list_all_kibana_api_paths y get_kibana_api_detail ). Este diseño garantiza la compatibilidad con clientes MCP que no pueden seleccionar varios recursos de forma inteligente, lo que facilita la interacción de herramientas como Claude Desktop con Kibana.
Consejo: Se recomienda a la mayoría de los usuarios utilizar el modo de herramienta para una experiencia más natural y potente; el modo de recurso ofrece la máxima flexibilidad para casos de uso avanzados y de compatibilidad.
Desarrollo
Instalar dependencias:
npm installConstruir el servidor:
npm run buildReconstrucción automática en modo de desarrollo:
npm run watchDepuración
Dado que el servidor MCP se comunica mediante stdio, la depuración puede resultar incómoda. Se recomienda usar MCP Inspector:
npm run inspectorDespués de iniciarse, Inspector proporcionará una URL de herramienta de depuración accesible desde el navegador.
Comunidad
Este proyecto es mantenido por la comunidad. ¡Agradecemos sus contribuciones y comentarios! Por favor, sea respetuoso e inclusivo en todas las comunicaciones y respete el Código de Conducta de la Comunidad Elastic .
Licencia
Este proyecto está licenciado bajo la Licencia Apache 2.0. Consulte el archivo de LICENCIA para más detalles.
Solución de problemas
Compruebe si la configuración de MCP es correcta
Asegúrese de que la dirección de Kibana sea accesible
Verificar que las credenciales de autenticación tengan permisos suficientes
Si utiliza una CA personalizada, asegúrese de que la ruta del certificado sea correcta y legible
Si utiliza
NODE_TLS_REJECT_UNAUTHORIZED=0, tenga en cuenta los riesgos de seguridadComprobar la salida de los mensajes de error en la terminal
Available Tools
6 toolsexecute_kb_apiC
Execute a custom API request for Kibana with multi-space support
| Name | Required | Description | Default |
|---|---|---|---|
| body | No | ||
| method | Yes | ||
| params | No | ||
| path | Yes | ||
| space | No | Target Kibana space (optional, defaults to configured space) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions 'multi-space support' which adds some context about space handling, but fails to describe critical behaviors like authentication requirements, rate limits, error handling, or what 'execute' entails (e.g., whether it's idempotent, what happens on failure). For a tool that can perform write operations (PUT, DELETE), this is inadequate.
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 a single, efficient sentence that front-loads the core purpose ('Execute a custom API request for Kibana') and adds a key feature ('with multi-space support'). There's no wasted language or redundancy.
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 the complexity (5 parameters, no output schema, no annotations, and support for write operations), the description is incomplete. It lacks information about return values, error conditions, authentication, and how to use parameters effectively. The mention of 'multi-space support' is helpful but insufficient for a tool with this scope and potential impact.
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 only 20% (only the 'space' parameter has a description), so the description must compensate. It adds minimal value by implying the tool handles 'multi-space' contexts, which relates to the 'space' parameter, but doesn't explain other parameters like 'body', 'params', 'method', or 'path' beyond what the schema provides. The baseline is 3 since schema coverage is low but the description doesn't fully compensate.
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 verb ('execute') and resource ('custom API request for Kibana'), specifying the action and target. However, it doesn't explicitly differentiate from siblings like 'get_kibana_api_detail' or 'list_all_kibana_api_paths', which appear to be read-only operations, while this tool supports multiple HTTP methods including write operations.
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 mentions 'multi-space support' but doesn't provide explicit guidance on when to use this tool versus alternatives. No context is given about prerequisites, when-not-to-use scenarios, or comparisons to sibling tools like 'get_available_spaces' or 'search_kibana_api_paths'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_available_spacesC
Get all available Kibana spaces with current context
| Name | Required | Description | Default |
|---|---|---|---|
| include_details | No | Include detailed space information (name, description, etc.) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states what the tool does but lacks details on permissions needed, rate limits, pagination, or what 'current context' entails. This is a significant gap for a tool that likely interacts with a Kibana API.
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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, making it easy to parse quickly.
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 and no output schema, the description is incomplete. It doesn't explain what 'available spaces' means, what 'current context' includes, or what the return values look like. For a tool that likely returns a list of Kibana spaces, more context is needed to guide the agent effectively.
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?
The schema description coverage is 100%, so the input schema already documents the 'include_details' parameter. The description doesn't add any parameter-specific information beyond what's in the schema, such as examples or edge cases, but the baseline is 3 when the schema does the heavy lifting.
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 verb 'Get' and the resource 'all available Kibana spaces with current context', making the purpose understandable. However, it doesn't explicitly differentiate this tool from its siblings like 'list_all_kibana_api_paths' or 'search_kibana_api_paths', which might also involve listing Kibana resources.
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. It doesn't mention any prerequisites, exclusions, or compare it to sibling tools like 'list_all_kibana_api_paths', leaving the agent to infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_kibana_api_detailC
Get details for a specific Kibana API endpoint
| Name | Required | Description | Default |
|---|---|---|---|
| method | Yes | HTTP method, e.g. GET, POST, PUT, DELETE | |
| path | Yes | API path, e.g. /api/actions/connector_types |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states what the tool does but doesn't describe how it behaves—such as whether it's read-only, what format the details are returned in, error handling, or any rate limits. This is a significant gap for a tool with no annotation coverage.
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 a single, efficient sentence that directly states the tool's purpose without any fluff. It's appropriately sized and front-loaded, making it easy to parse quickly.
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 the complexity of querying API endpoints and the lack of annotations and output schema, the description is insufficient. It doesn't explain what 'details' include, how results are structured, or any behavioral aspects like safety or performance, leaving the agent with incomplete information for proper use.
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?
The schema description coverage is 100%, with both parameters ('method' and 'path') well-documented in the schema. The description adds no additional meaning beyond implying that these parameters identify a specific endpoint, which is already clear from the schema. This meets the baseline for high schema coverage.
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 verb ('Get details') and resource ('specific Kibana API endpoint'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'list_all_kibana_api_paths' or 'search_kibana_api_paths' which also deal with Kibana API endpoints, so it doesn't fully distinguish itself from alternatives.
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 like 'list_all_kibana_api_paths' or 'execute_kb_api'. It doesn't mention prerequisites, context, or exclusions, leaving the agent to infer usage based on the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_statusB
Get Kibana server status with multi-space support
| Name | Required | Description | Default |
|---|---|---|---|
| space | No | Target Kibana space (optional, defaults to configured space) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states what the tool does but lacks behavioral details: it doesn't specify if this is a read-only operation, what permissions are required, whether it affects system state, rate limits, or what the output format looks like (e.g., JSON structure, error handling). For a tool with no annotation coverage, this is a significant gap in transparency.
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 a single, efficient sentence that front-loads the core purpose ('Get Kibana server status') and adds a key feature ('with multi-space support'). There is no wasted verbiage, and it's appropriately sized for a simple tool with one optional parameter.
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 the tool's low complexity (1 optional parameter, no output schema, no annotations), the description is minimally complete. It covers the basic purpose but lacks context on usage guidelines, behavioral traits, or output details. For a status-checking tool, it should ideally mention what 'status' entails (e.g., health metrics, version info) or how it differs from siblings, but it's adequate as a starting point.
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 100%, with the single parameter 'space' documented in the schema as optional and defaulting to configured space. The description adds minimal value beyond this by mentioning 'multi-space support', which implies the parameter's purpose but doesn't provide additional syntax or format details. Baseline 3 is appropriate as the schema handles parameter documentation adequately.
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 verb ('Get') and resource ('Kibana server status'), making the purpose evident. It adds specificity with 'multi-space support' which distinguishes it from generic status tools. However, it doesn't explicitly differentiate from sibling tools like 'get_kibana_api_detail' or 'execute_kb_api', which might also retrieve status-related information.
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. It mentions 'multi-space support' but doesn't explain if this is for checking overall server health, space-specific status, or when to prefer it over siblings like 'get_available_spaces' or 'execute_kb_api'. No explicit when/when-not instructions or prerequisites are included.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_all_kibana_api_pathsB
List all Kibana API endpoints as a resource list
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states what the tool does but doesn't describe important behavioral traits like whether this is a read-only operation, what format the resource list returns, whether there are rate limits, or if authentication is required. The description is functional but lacks operational context.
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 a single, efficient sentence that communicates the core functionality without any wasted words. It's appropriately sized for a zero-parameter tool and front-loads the essential information ('List all Kibana API endpoints').
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?
For a zero-parameter tool with no output schema, the description adequately states what the tool does but lacks important context about the return format, behavioral characteristics, and differentiation from sibling tools. Given the complexity of API endpoint listing and the absence of annotations/output schema, the description should provide more operational guidance to be truly complete.
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?
The tool has 0 parameters with 100% schema description coverage, so the baseline is 4. The description appropriately doesn't discuss parameters since none exist, and the schema fully documents this absence without needing additional explanation in the description.
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 ('List all') and resource ('Kibana API endpoints as a resource list'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'search_kibana_api_paths' or 'get_kibana_api_detail', which would require more specific scope information.
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 like 'search_kibana_api_paths' or 'get_kibana_api_detail'. There's no mention of use cases, prerequisites, or comparisons with sibling tools, leaving the agent without contextual usage information.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_kibana_api_pathsC
Search Kibana API endpoints by keyword
| Name | Required | Description | Default |
|---|---|---|---|
| search | Yes | Search keyword for filtering API endpoints |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool searches endpoints by keyword, but doesn't describe behavioral traits such as whether it's read-only, safe to use, what the output format looks like (e.g., list of paths, details), or any limitations (e.g., search scope, rate limits). For a tool with zero annotation coverage, this is a significant gap in transparency.
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 a single, efficient sentence: 'Search Kibana API endpoints by keyword'. It's front-loaded with the core action and resource, with zero wasted words. Every part of the sentence earns its place by conveying essential purpose, making it highly concise and well-structured.
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 the tool's complexity (a search function with one parameter) and the lack of annotations and output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., a list of endpoint paths, details, or matches), how results are formatted, or any behavioral context needed for effective use. This leaves significant gaps for the agent to understand the tool's full context.
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?
The input schema has 100% description coverage, with the single parameter 'search' documented as 'Search keyword for filtering API endpoints'. The description adds no additional meaning beyond this, as it only repeats the keyword concept without elaborating on syntax, format, or examples. Given the high schema coverage, the baseline score of 3 is appropriate, as the schema does the heavy lifting.
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 tool's purpose: 'Search Kibana API endpoints by keyword'. It specifies the verb ('search'), resource ('Kibana API endpoints'), and mechanism ('by keyword'), which is specific and actionable. However, it doesn't explicitly differentiate from sibling tools like 'list_all_kibana_api_paths' or 'get_kibana_api_detail', which prevents a perfect 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. It doesn't mention sibling tools like 'list_all_kibana_api_paths' (which might list all endpoints without filtering) or 'get_kibana_api_detail' (which might retrieve details for a specific endpoint), leaving the agent to infer usage context. This lack of explicit when-to-use or alternative references results in minimal guidance.
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.
6 tool updates
v1.0.0- First observed
execute_kb_api - First observed
get_available_spaces - First observed
get_kibana_api_detail - First observed
get_status - First observed
list_all_kibana_api_paths - First observed
search_kibana_api_paths
TDQS
Scored across 6 tools
Each tool has a clearly distinct purpose with no overlap: execute_kb_api performs custom API calls, get_available_spaces lists spaces, get_kibana_api_detail provides endpoint details, get_status checks server status, list_all_kibana_api_paths enumerates all endpoints, and search_kibana_api_paths searches endpoints. The descriptions reinforce these unique functions, making misselection unlikely.
All tools follow a consistent verb_noun pattern with snake_case: execute_kb_api, get_available_spaces, get_kibana_api_detail, get_status, list_all_kibana_api_paths, and search_kibana_api_paths. The naming is predictable and readable throughout the set, with no deviations in style or convention.
With 6 tools, the count is well-scoped for a Kibana MCP server focused on API exploration and execution. Each tool earns its place by covering distinct aspects like status, spaces, endpoint listing, searching, detailing, and execution, avoiding bloat while providing comprehensive functionality.
The tool set is highly complete for exploring and interacting with Kibana APIs, covering discovery (list/search), details, spaces, status, and execution. A minor gap exists in lacking direct CRUD operations for Kibana objects like dashboards or visualizations, but agents can work around this using execute_kb_api for custom requests.
Maintenance
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