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jerrelblankenship

Kibana MCP Server

list_data_views

Retrieve all available data views (index patterns) from Kibana to access and analyze Elasticsearch data sources.

Instructions

List all data views (index patterns) in Kibana

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The handler for the 'list_data_views' tool, which calls the kibanaClient and formats the output.
    case 'list_data_views': {
      const dataViews = await kibanaClient.listDataViews();
    
      return {
        content: [
          {
            type: 'text' as const,
            text: JSON.stringify(
              {
                total: dataViews.total,
                dataViews: dataViews.saved_objects.map((dv) => ({
                  id: dv.id,
                  title: dv.attributes.title,
                  timeFieldName: dv.attributes.timeFieldName,
                })),
              },
              null,
              2
            ),
          },
        ],
      };
    }
  • Tool registration for 'list_data_views' in the MCP server setup.
      name: 'list_data_views',
      description: 'List all data views (index patterns) in Kibana',
      inputSchema: {
        type: 'object',
        properties: {},
      },
    },
  • The KibanaClient implementation that performs the actual API request to list index patterns (data views).
    async listDataViews(): Promise<SavedObjectsResponse<KibanaDataView>> {
      const response = await this.axiosInstance.get('/api/saved_objects/_find', {
        params: {
          type: 'index-pattern',
          per_page: 100,
        },
      });
    
      return response.data;
    }
Behavior2/5

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 this is a listing operation, implying it's likely read-only and non-destructive, but doesn't confirm this or add any context about permissions, rate limits, pagination, or return format. This leaves significant gaps for a tool with zero 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.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core purpose without any wasted words. It's appropriately sized for a simple listing tool with no parameters, making it easy for an agent to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is minimally adequate. It states what the tool does but lacks behavioral details and usage guidance. For a basic listing operation, this might suffice, but the absence of annotations means more context would be helpful for reliable agent use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, and since there are none, it doesn't need to compensate for any gaps, earning a baseline score above the minimum.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

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 ('data views (index patterns) in Kibana'), making the purpose immediately understandable. However, it doesn't differentiate this tool from sibling tools like 'list_dashboards' or 'list_visualizations' beyond naming the specific resource type, 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.

Usage Guidelines2/5

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 prerequisites, context for selecting this over other listing tools, or any exclusions, leaving the agent to infer usage based solely on the tool name and resource type.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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