Kibana Log Analysis & API Dashboard MCP Server
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Kibana Log Analysis & API Dashboard MCP ServerSearch logs for recent errors in payment-service"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Kibana Log Analysis & API Dashboard MCP Server
An MCP (Model Context Protocol) server designed for enterprise developers to connect local AI assistants directly to Elasticsearch, Kibana, and local codebases.
⚠️ For New Developers & Forkers
If you have just cloned this repository to use within your organization, search the codebase for TODO: comments. There are several places where data or settings should be manually updated to fit your company's architecture.
The most crucial manual updates inside src/index.ts include:
Log Schema Customization: Update the
.levelorhttp.response.status_codefields to match your company's logging convention.Self-Signed Certificates: Add your internal CA cert path if your Elasticsearch instance does not use public SSL certificates.
Regex Parsers for
.NETorGo: If your team uses languages other than Java/Typescript, update thescan_code_for_apistool regex.
Features
search_logs: Search Elasticsearch indices using keywords and Lucene queries.get_log_details: Retrieve the full un-truncated JSON of specific log events.analyze_service_health: Aggregate error rates, success rates, and HTTP status codes for a given service.scan_code_for_apis: Scans your local Spring Boot (Java) or Express (Node.js) project to dynamically discover REST endpoints.create_api_dashboard: Programmatically generates a Kibana dashboard visualizing the dynamically discovered endpoints using the Kibana Saved Objects API.
Installation & Production Setup
Ensure you have Node.js (v18+) installed.
Run
npm installRun
npm run buildCopy
.env.exampleto.envand configure your environment variables (or set them directly in your LLM Client setup).
Configuration Map
Variable | Description |
| URL to your Elasticsearch cluster (e.g., |
| Auth Token with specific read scopes. |
| URL to your Kibana instance. |
Usage with Claude Desktop / Cursor
Add the following configuration to your claude_desktop_config.json or Cursor MCP settings:
{
"mcpServers": {
"kibana-logs": {
"command": "node",
"args": ["/Users/sidhu/.gemini/antigravity/scratch/kibana-mcp-server/build/index.js"],
"env": {
"ELASTIC_URL": "https://your-bank-cluster:9200",
"ELASTIC_API_KEY": "your_secure_api_key",
"KIBANA_URL": "https://your-bank-kibana:5601"
}
}
}
}Security Best Practices for Enterprise
Least Privilege: Do not grant your
ELASTIC_API_KEYdelete, put, or cluster-admin privileges. It only needsreadon application indices, andallaccess to the Kibana Saved Objects API (to create dashboards).Data Masking: If your logs contain PII (Personally Identifiable Information), you should implement a regex mask in
src/index.tsright before returning the logs to the AI payload.
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