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Search Elasticsearch errors, detect patterns, and trace root causes.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "es-error-lens" yet — see the docs or source repo.
Search Elasticsearch logs for errors from the last 24 hours, group common patterns, and suggest likely root-cause clues.
Returns relevant error logs, recurring patterns, and initial root-cause analysis.
Analyze the error-rate trend for the past week, identify spikes, and list the corresponding log context.
Outputs error-rate trends, spike periods, and linked logs.
Using this error log, retrieve the full trace context to pinpoint the failing step in the request chain.
Returns the full trace and related error context.
SREs or backend developers can use it after an alert fires to quickly search related errors and inspect full context. It is suited for extracting actionable debugging clues from large Elasticsearch log volumes.
When the same errors keep recurring, it can summarize repeated patterns and observe error-rate changes to tell whether the issue is sporadic or systemic.
When you only have a single error log, it can fetch the full trace so the context is richer and the failing step is easier to identify.
It searches and analyzes errors in Elasticsearch logs, detects recurring patterns, analyzes error-rate trends, and retrieves full trace context. It is suited for incident debugging and error attribution.
You need access to Elasticsearch log data and use it through MCP tool calls. For exact integration or deployment details, see the source repository.
It does more than retrieve individual logs: it analyzes recurring errors, trend changes, and full trace context. The focus is helping LLM agents find root causes faster.
Classify MCP errors and provide recovery guidance with actionable retry and state details.
Use natural language to search, analyze, and manage Elasticsearch data.
Connect to Elasticsearch via MCP for search, index inspection, and cluster info.
Connect to Elasticsearch for querying, search analysis, and workflow automation.
A local-first MCP server for tracking and reviewing errors systematically.
Interact with Elasticsearch for health checks, index management, CRUD, and search.