Kibana

v0.7.3Monitoring & Observabilitystable

Enables AI assistants to interact with Kibana dashboards, visualizations, and Elasticsearch data through read-only resources and executable tools for searching logs, exporting dashboards, and querying data.

kibanamcpmcp-serverelasticsearchmodel-context-protocol
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What is Kibana?

Kibana is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to enables ai assistants to interact with kibana dashboards, visualizations, and elasticsearch data through read-only resources and executable tools for searching logs, exporting dashboards, and querying...

Enables AI assistants to interact with Kibana dashboards, visualizations, and Elasticsearch data through read-only resources and executable tools for searching logs, exporting dashboards, and querying data.

This server falls under the Monitoring & Observability and Search & Data Extraction categories on MCPgee, the world's largest MCP server directory with 33,000+ servers.

Features

  • Enables AI assistants to interact with Kibana dashboards, vi

Use Cases

Query Elasticsearch data and logs through Kibana.
Export and analyze dashboard visualizations.
Search and correlate log data naturally.
TocharianOU

Maintainer

LicenseApache 2.0
Languagetypescript
Versionv0.7.3
UpdatedMay 21, 2026
Statushealthy
Maintenanceactive

Works with

ClaudeOpenAIwindowsmacoslinux

Installation

NPM

npx -y @tocharianou/mcp-server-kibana

Manual Installation

npx -y @tocharianou/mcp-server-kibana

Configuration

Configuration Details

Config File

claude_desktop_config.json

Performance

Response Metrics

Response Time< 200ms
ThroughputMedium

Resource Usage

Memory UsageLow
CPU UsageLow

How to Set Up and Use Kibana

The Kibana MCP Server bridges AI assistants to your Kibana and Elasticsearch stack, exposing read and write capabilities for dashboards, visualizations, saved objects, and raw Elasticsearch queries through natural language. It supports API key, basic auth, and cookie-based authentication so it can connect to both on-prem and Elastic Cloud deployments. Teams use it to investigate incidents, analyze log data, and manage Kibana assets without leaving their AI chat interface.

Prerequisites

  • Node.js 18.0.0 or later installed
  • A running Kibana instance (local or Elastic Cloud) with network access from your machine
  • A Kibana API key, or username/password credentials with appropriate permissions
  • An MCP-compatible client such as Claude Desktop or Cursor
1

Verify Kibana connectivity

Confirm your Kibana instance is reachable and note the base URL (e.g. http://localhost:5601 or https://your-cloud-id.kb.us-east-1.aws.elastic-cloud.com).

curl http://localhost:5601/api/status
2

Obtain authentication credentials

In Kibana, navigate to Stack Management > API Keys and create a key with the necessary privileges. Alternatively, note an existing username and password. The server prioritizes API key over basic auth over session cookies.

3

Add the server to your MCP client configuration

Edit claude_desktop_config.json and add the Kibana MCP server block, supplying your Kibana URL and chosen authentication method.

{
  "mcpServers": {
    "kibana": {
      "command": "npx",
      "args": ["-y", "@tocharianou/mcp-server-kibana"],
      "env": {
        "KIBANA_URL": "http://localhost:5601",
        "KIBANA_API_KEY": "your_encoded_api_key",
        "KIBANA_DEFAULT_SPACE": "default"
      }
    }
  }
}
4

Restart your MCP client

Restart Claude Desktop (or your IDE) so it starts the Kibana MCP server process and registers the available tools.

5

Verify the connection

Ask the assistant to get the Kibana status. This calls the get_status tool and confirms the server can reach your Kibana instance.

Kibana Examples

Client configuration

Minimal Claude Desktop configuration using API key authentication. For basic auth, replace KIBANA_API_KEY with KIBANA_USERNAME and KIBANA_PASSWORD.

{
  "mcpServers": {
    "kibana": {
      "command": "npx",
      "args": ["-y", "@tocharianou/mcp-server-kibana"],
      "env": {
        "KIBANA_URL": "http://localhost:5601",
        "KIBANA_API_KEY": "your_encoded_api_key",
        "KIBANA_DEFAULT_SPACE": "default",
        "KIBANA_TIMEOUT": "30000"
      }
    }
  }
}

Prompts to try

These prompts demonstrate the server's dashboard management, log querying, and health check capabilities.

- "What is the current status of my Kibana server?"
- "Search for all dashboards that contain the word 'sales'."
- "Check the health of the dashboard named 'Infrastructure Overview'."
- "List all saved objects of type index-pattern."
- "Show me the dependencies for the 'Revenue Metrics' dashboard."

Troubleshooting Kibana

Connection refused or ECONNREFUSED errors

Verify that KIBANA_URL is correct and that Kibana is running. For HTTPS endpoints with self-signed certificates, set KIBANA_CA_CERT to the path of your CA file or set NODE_TLS_REJECT_UNAUTHORIZED=0 (only for development).

401 Unauthorized when using API key

Kibana expects the API key in encoded form (base64 of 'id:api_key'). In the Kibana console, copy the 'encoded' value shown after creating the key, not the raw key ID.

Tools not appearing in the AI client

Ensure Node.js 18+ is installed and accessible in the PATH used by your MCP client. Run 'npx -y @tocharianou/mcp-server-kibana' in a terminal to confirm it starts without errors before adding it to the config.

Frequently Asked Questions about Kibana

What is Kibana?

Kibana is a Model Context Protocol (MCP) server that enables ai assistants to interact with kibana dashboards, visualizations, and elasticsearch data through read-only resources and executable tools for searching logs, exporting dashboards, and querying data. It connects AI assistants to external tools and data sources through a standardized interface.

How do I install Kibana?

Install via npm with the command: npx -y @tocharianou/mcp-server-kibana. Then add the server configuration to your AI client's JSON config file (e.g., claude_desktop_config.json or .cursor/mcp.json).

Which AI clients work with Kibana?

Kibana works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.

Is Kibana free to use?

Yes, Kibana is open source and available under the Apache 2.0 license. You can use it freely in both personal and commercial projects.

Browse More Monitoring & Observability MCP Servers

Explore all monitoring & observability servers available in the MCPgee directory. Each server includes setup guides for Claude, Cursor, and VS Code.

Quick Config Preview

{ "mcpServers": { "kibana-mcp-server": { "command": "npx", "args": ["-y", "@tocharianou/mcp-server-kibana"] } } }

Add this to your claude_desktop_config.json or .cursor/mcp.json

Read the full setup guide →

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