README.md
Create and manage Kibana dashboards, Lens visualizations, and data views.
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_data_views |
List existing Kibana data views |
create_data_view |
Create a new data view for an index |
list_dashboards |
List existing dashboards |
get_dashboard |
Get a dashboard's full definition |
create_lens_visualization |
Create a Lens visualization (bar, line, metric, donut, etc.) |
create_dashboard |
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.py
Architecture
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 views
Also compatible with Claude Desktop, Cursor, VS Code via:
https://your-cluster.kb.../api/agent_builder/mcp
Tools (6)
list_data_viewsList existing Kibana data viewscreate_data_viewCreate a new data view for an indexlist_dashboardsList existing dashboardsget_dashboardGet a dashboard's full definitioncreate_lens_visualizationCreate a Lens visualization (bar, line, metric, donut, etc.)create_dashboardAssemble visualizations into a dashboardEnvironment Variables
KIBANA_ENDPOINTrequiredThe URL of your Kibana instanceELASTIC_API_KEYrequiredBase64 encoded Elastic API keyELASTIC_CLOUD_ENDPOINTThe URL of your Elastic Cloud instanceConfiguration
claude_desktop_config.json
{"mcpServers": {"kibana": {"command": "python", "args": ["main.py"], "env": {"KIBANA_ENDPOINT": "https://your-cluster.kb.us-east-2.aws.elastic-cloud.com", "ELASTIC_API_KEY": "your-base64-api-key"}}}}Try it
→List all existing dashboards in my Kibana instance.
→Create a new Lens bar chart visualization showing the count of logs over the last 24 hours.
→Create a new dashboard named 'System Health' and add the existing 'CPU Usage' visualization to it.
→List all available data views to see which indices are currently configured.