"Collecting and Analyzing Server-Side Errors Based on MySQL, Redis, and Elasticsearch" matching MCP servers:

Enables interaction with Google Cloud services including billing cost analysis, log querying, and metrics monitoring through natural language commands. Provides comprehensive tools for managing GCP resources, analyzing costs, detecting anomalies, and retrieving operational insights.

Transforms Elasticsearch into an AI-powered observability engine for analyzing logs, APM traces, and system metrics through natural language.

A lightweight npm MCP server for deep Redis diagnostics, offering tools for memory, slowlog, clients, keyspace, latency, and config analysis with AI-powered recommendations.

FastMCP server with read-only tools to monitor Redis — queue depths, Celery queue status, connected clients, server/memory info, and per-database key counts

Read-only MCP server that converts Elasticsearch logs into citable evidence for AI agents, offering deterministic log summarization and search tools.

Governed MySQL + MariaDB DBA operations — slow-query, lock-wait/deadlock, replication, and fragmentation RCA, with unbypassable audit logging (MCP + CLI), budget/runaway guards, dry-run, and undo/rollback.

Enables any MCP-compatible agent to query, diagnose, map, and operate Elasticsearch or OpenSearch clusters via REST, with read-only defaults and layered safety controls.

Read-only MCP server for Elasticsearch log querying. Enables natural language search, filtering, context retrieval, and aggregation of logs.

A production-oriented reliability, benchmarking, and evaluation system that layers multi-version protocol negotiation, adaptive streaming, connection pooling, and resilience onto an MCP agent runtime.

MCP server that diagnoses ML model regressions by correlating drift reports, eval runs, and deploy logs, providing evidence-cited incident reports through a set of investigation tools.

Enables ingestion and full-text search of Windows application logs via MCP tools. Supports dual-backend indexing with Elasticsearch and SQLite for fast retrieval.

Exposes an observability REST API as MCP tools, enabling incident investigation through automated correlation of deploys with errors, log and metrics queries.

Enables Claude to discover and understand infrastructure-as-code drift by listing projects with drift, analyzing Terraform plan outputs, and providing remediation information.

Enables AI assistants to query Grafana datasources (Prometheus/Loki metrics and SQL databases like ClickHouse/Postgres/MySQL) and search or inspect dashboards through natural language, using read-only access to Grafana's API.

An MCP server that enables AI agents to safely operate multi-cluster Kubernetes fleets through an Open Cluster Management hub, with policy enforcement, human approval, and audit tracing.

Enables AI assistants to search Elasticsearch logs, retrieve log details, analyze service health, scan local codebases for APIs, and create Kibana dashboards.

Provides AI coding agents with real-time visibility into local development runtime state, enabling them to tail application logs, inspect ports, monitor process metrics, and diagnose network errors.

A comprehensive MCP server providing over 26 tools for querying, monitoring, and analyzing NewRelic data through NRQL queries and entity management. It enables interaction with NewRelic's NerdGraph API for managing alerts, logs, and incidents directly within Claude Code sessions.

MCP server for On-Call Health burnout analysis. Connects AI assistants to your on-call data for workload insights.

A JVM monitoring and control platform server based on Arthas that provides a Python interface for monitoring and analyzing Java processes with capabilities for thread analysis, memory monitoring, and performance diagnostics.