"Understanding Requirement Analysis" matching MCP servers:

Collects page performance metrics using Playwright, CDP, and Lighthouse, and returns a normalized PerformanceReport.

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

Enables read-only triage of Microsoft Entra ID sign-in and audit logs through fixed tools for sign-in failure analysis, user lookup, directory audits, and daily briefs.

MCP server that diagnoses Apache Spark job failures and optimizes performance using stack-trace analysis and LLM providers, supporting EMR and local sources.

Enables analysis of JVM thread dumps to detect deadlocks, CPU spikes, pool exhaustion, and virtual thread pinning, returning a health score and interactive report link.

An MCP server that connects language models to a Wazuh SIEM cluster, enabling read-only plain-language queries, schema inspection, field coverage analysis, and decoder testing.

Enables monitoring and analysis of agent goal achievement and failures across sessions, repos, and tools, with detailed views and tracing.

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

MCP server that provides read-only analysis of Claude Code session transcripts, enabling queries about project activity, session details, and tool usage.

AI-powered incident management MCP server that enables investigation, root cause analysis, and response actions for production incidents using mocked data for demo purposes.

MCP server wrapping the Akamai mPulse Query API v2 to fetch RUM aggregate data (summaries, histograms, per-minute time series) with loss-free numbers for downstream statistical analysis.

Provides read-only access to host system metrics (CPU, memory, disk), Docker container health/logs, and sandboxed log file analysis via MCP tools, enabling AI agents to monitor enterprise infrastructure safely.

Provides cost analysis of AI agent usage by previewing scrubbed metadata before upload and analyzing spend, cache-hit rates, and waste recovery through a local or remote server.

Enables AI clients to run read-only network diagnostics over a sample multi-site topology, including site health, degraded sites, root-cause analysis, and redundancy gap detection.

Exposes a materialized service dependency graph as an MCP toolset for persistent, queryable root-cause analysis via Cypher queries.

An MCP server for AI-powered log analysis that enables parsing, searching, and debugging across nine log formats directly within Claude. It features automated error extraction, sensitive data scanning, and streaming support for large log files.

MCP server that gives AI agents access to your application's OpenTelemetry traces for querying, analysis, and debugging.

Lets AI agents query, manage, and operate their LLM observability data directly from the conversation. Provides 87 tools for cost analysis, alerting, anomaly detection, and runtime control gates.

Enables agents to check whether an execution trace contains the evidence needed for post-hoc causal reconstruction, retrieve individual requirement details, and list evidence requirements per failure class over MCP stdio. It works on files, directories, or inline JSON locally and never transmits or persists data.

Enables causal root cause analysis with 56 tools covering causal graph construction, 10 RCA model families plus 3 dedicated PyRCA algorithms (Salesforce PyRCA, BSD-3-Clause), multi-model consensus, and PDF/HTML/Excel/Markdown report generation. Works with Claude, Ollama, Groq, OpenAI, Gemini, LangChain, Cursor — 10 providers.