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kibana-mcp
Advanced tools
MCP server for Kibana / Elasticsearch — log search, aggregations, index discovery, dashboards.
MCP server for Kibana / Elasticsearch — log search, aggregations, index discovery, and dashboard browsing via Claude and any MCP-compatible agent.
Existing integrations require a running Kibana instance with browser-level credentials and often wrap the Kibana UI rather than the stable REST APIs. This server:
outputSchema) and markdown text so it works with any MCP clientreadOnlyHint: true, no data is modified| Tool | API | Description |
|---|---|---|
kibana_list_indices | GET ES/_cat/indices | Discover available indices with health, docs, size |
kibana_search_logs | POST ES/{index}/_search | Full-text log search with time range, sort, size |
kibana_aggregate_logs | POST ES/{index}/_search | Terms grouping with count/avg/sum/min/max metric |
kibana_list_dashboards | GET Kibana/api/saved_objects/_find | List saved dashboards with search + pagination |
kibana_get_dashboard | GET Kibana/api/saved_objects/dashboard/{id} | Fetch one dashboard with panel breakdown |
pip install kibana-mcp
Or run directly with uvx:
uvx kibana-mcp
| Variable | Required | Description |
|---|---|---|
KIBANA_URL | Yes | Kibana base URL (e.g. https://kibana.example.com) |
ELASTICSEARCH_URL | No | Direct ES endpoint. If unset, ES requests go through Kibana Console proxy |
KIBANA_API_KEY | No | ES API key (ApiKey base64(id:api_key) format). Recommended for agents |
KIBANA_USERNAME | No | HTTP Basic auth username (used if API key not set) |
KIBANA_PASSWORD | No | HTTP Basic auth password |
KIBANA_SSL_VERIFY | No | true (default) or false for self-signed certificates |
Auth priority: ApiKey > Basic > anonymous.
Copy .env.example to .env and fill in your values.
{
"mcpServers": {
"kibana": {
"command": "uvx",
"args": ["kibana-mcp"],
"env": {
"KIBANA_URL": "https://kibana.example.com",
"KIBANA_API_KEY": "your-api-key-here"
}
}
}
}
Or with direct ES access for better performance:
{
"mcpServers": {
"kibana": {
"command": "uvx",
"args": ["kibana-mcp"],
"env": {
"KIBANA_URL": "https://kibana.example.com",
"ELASTICSEARCH_URL": "https://es.example.com:9200",
"KIBANA_API_KEY": "your-api-key-here"
}
}
}
}
docker run --rm -i \
-e KIBANA_URL=https://kibana.example.com \
-e KIBANA_API_KEY=your-key \
ghcr.io/mshegolev/kibana-mcp
Find the last 50 ERROR logs from the API service in the last hour
→ kibana_search_logs(index="logs-*", query="level:ERROR AND service:api", size=50, time_from="2026-04-18T09:00:00Z")
Show 500 HTTP errors sorted oldest first for incident replay
→ kibana_search_logs(index="nginx-*", query="status:500", sort_order="asc", size=100)
How many logs per log level in the last hour?
→ kibana_aggregate_logs(index="logs-*", group_by="level", time_from="2026-04-18T09:00:00Z")
What is the average response time per service?
→ kibana_aggregate_logs(index="logs-*", group_by="service.keyword", metric="avg", metric_field="response_time_ms")
What log indices are available?
→ kibana_list_indices()
Show me all filebeat indices
→ kibana_list_indices(pattern="filebeat-*")
Find the infrastructure dashboard
→ kibana_list_dashboards(search="infrastructure")
What panels does dashboard X have?
→ kibana_get_dashboard(dashboard_id="<id from list_dashboards>")
kibana_search_logs): typically 50-500ms with direct ES URL; add 100-200ms when routing through Kibana Console proxykibana_aggregate_logs): size:0 queries — no hits transferred, usually 10-100ms_cat/indices call, O(index_count) response, typically <100msELASTICSEARCH_URL directly if your agent does frequent log searches — eliminates the proxy overheadgit clone https://github.com/mshegolev/kibana-mcp
cd kibana-mcp
pip install -e '.[dev]'
pytest tests/ -v
ruff check src tests
ruff format src tests
MIT — see LICENSE.
FAQs
MCP server for Kibana / Elasticsearch — log search, aggregations, index discovery, dashboards.
The pypi package kibana-mcp receives a total of 146 weekly downloads. As such, kibana-mcp popularity was classified as not popular.
We found that kibana-mcp demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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