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 Dashboard Buildercreate a donut chart for log levels and add it to the monitoring dashboard"
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 Dashboard Builder — MCP Server
A Model Context Protocol (MCP) server that gives the Elastic Dashboard Architect AI agent the ability to create Kibana dashboards, Lens visualizations, and data views via the Kibana Saved Objects API.
Tools Exposed
Tool | Description |
| List existing Kibana data views |
| Create a new data view for an index |
| List existing dashboards |
| Get a dashboard's full definition |
| Create a Lens visualization (bar, line, metric, donut, etc.) |
| Assemble visualizations into a dashboard |
Deploy to Render.com (Free — 5 minutes)
Push this repo to GitHub
cd /path/to/kibana-mcp-server git init && git add . && git commit -m "Initial commit" gh repo create kibana-mcp-server --public --pushGo to render.com → New → Web Service
Connect your GitHub repo
Render auto-detects
render.yaml
Set Environment Variables in Render dashboard:
KIBANA_ENDPOINT = https://your-cluster.kb.us-east-2.aws.elastic-cloud.com ELASTIC_API_KEY = your-base64-api-key ELASTIC_CLOUD_ENDPOINT = https://your-cluster.es.us-east-2.aws.elastic-cloud.comCopy your Render URL (e.g.
https://kibana-mcp-server.onrender.com)Update the Kibana MCP connector to point to your Render URL:
curl -X PUT "https://your-cluster.kb.../api/actions/connector/YOUR_CONNECTOR_ID" \ -H "Authorization: ApiKey YOUR_API_KEY" \ -H "kbn-xsrf: true" \ -H "Content-Type: application/json" \ -H "elastic-api-version: 2023-10-31" \ -d '{ "name": "Kibana Dashboard Builder", "config": {"serverUrl": "https://kibana-mcp-server.onrender.com", "headers": {"Content-Type": "application/json"}}, "secrets": {} }'Done. The Dashboard Architect agent now has a permanent, always-available backend.
Local Development
pip install -r requirements.txt
KIBANA_ENDPOINT=https://... ELASTIC_API_KEY=... python main.pyArchitecture
Dashboard Architect (Kibana AI Agent)
↓ calls tools via
Kibana .mcp connector
↓ HTTP POST to
THIS SERVER (Render.com — permanent HTTPS URL)
↓ calls Kibana Saved Objects API
Kibana → creates dashboard, lens viz, data viewsAlso compatible with Claude Desktop, Cursor, VS Code via:
https://your-cluster.kb.../api/agent_builder/mcpThis server cannot be installed
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.