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Let LLMs read dashboard objects and query logs via OpenSearch Dashboards.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "opensearch-dashboard-mcp" yet — see the docs or source repo.
Use OpenSearch Dashboards to query logs from the last hour containing "error" and return the latest 20 entries in reverse chronological order.
A list of matching log entries with timestamps and brief log content summaries.
Read saved objects in OpenSearch Dashboards and list the available dashboard and visualization names.
A list of saved objects, such as dashboard and visualization names.
List the accessible tenants and index patterns in OpenSearch Dashboards so I can confirm the available query scope.
A list of tenants and index patterns for choosing the data scope of later queries.
DevOps engineers or developers can have an LLM query logs through OpenSearch Dashboards to quickly locate abnormal time ranges or error keywords. This reduces manual console switching and repetitive searching.
When a team needs to understand existing dashboards, visualizations, and other saved objects, this tool can read and list them centrally. It is useful for environment reviews or handoff preparation.
Before running log queries, data analysts or DevOps staff can list tenants and index patterns to confirm the accessible data scope for the current connection. This helps avoid querying the wrong tenant or index.
It enables LLM clients to interact with OpenSearch Dashboards. Known capabilities include reading saved objects, listing tenants and index patterns, and querying logs through the Dashboards API.
Based on the description, it depends on OpenSearch Dashboards and its API for interaction. For exact installation steps, authentication requirements, or configuration details, see the source repository.
From the given information, it is designed for interaction with OpenSearch Dashboards rather than only describing a lower-level query interface. Whether it adds more abstraction or constraints, see the source repository.
Search, aggregate, and explore OpenSearch logs and index metadata read-only.
Retrieve error stack traces from OpenSearch logs by transaction ID.
Query live OpenAPI docs, endpoints, and schemas for backend services.
Use natural language to search, analyze, and manage Elasticsearch data.
Query and analyze telemetry data in natural language to find performance issues.
Explore Kubernetes metrics, logs, traces, and service graphs to diagnose issues.