"Stack Exchange" matching MCP servers:

Health doctor for a home AI stack (Ollama nodes, GPUs, tailnet) with graded confidence, as a CLI, an MCP server and a DSH plugin.

MCP server for profiling Python processes using py-spy, supporting flamegraphs, stack dumps, and performance comparisons.

Enables AI assistants to run real Exchange Management Shell tasks against on-premise Microsoft Exchange for administration, monitoring, and troubleshooting, including recipient provisioning, transport troubleshooting, and DAG/health monitoring.

Enables an AI assistant to query local AI stack status, incidents, logs, GPU metrics, and service history, and to trigger restarts through MCP tools.

Enables AI agents to independently audit a trading bot's exchange account read-only, cross-checking raw exchange positions and orders against bot beliefs to surface missing or undersized stop losses, ghost trades, duplicate or orphaned orders, and size mismatches, with a hash-sealed attestation record for disputes and post-mortems. It never places, edits, or cancels orders, and reports a critical failure rather than a false clean result when the exchange cannot be read.

Provides 45 tools for monitoring and managing a Docker-based media stack, including Sonarr, Radarr, and other services.

A token-efficient MCP server for MySQL, PostgreSQL, and SQLite, providing tools to query databases, execute SQL, and analyze query performance.

Enables retrieval of error stack traces by transaction ID from OpenSearch logs, supporting configurable connection settings and Docker deployment.

Enables querying and searching logs from Kibana (ELK stack) via MCP, with support for project-based data views, trace ID correlation, and log expansion.

A production-oriented, read-only MCP server for secure ELK stack analysis, compatible with OpenClaw.

An MCP server that connects to Sentry.io or self-hosted Sentry instances to retrieve and analyze error reports, stack traces, and debugging information.

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

An MCP server for the ProveTrade trade-audit stack that lets models validate CSVs, run paid audit runs, and check service health/deploy status via typed tools.

Software end-of-life intelligence for AI agents: EOL dates, support timelines and 0-100 upgrade risk scores for 480+ products. Check whether a version is still supported, score its risk, or audit an entire stack.

Enables AI to dynamically search, describe, and execute 2000+ ZStack Cloud APIs, plus query monitoring metrics and data.

Real-time world state and independent API quality ratings (0-100) for AI trading agents. Exchange status, volatility (VIX/VVIX/SKEW), economic events, and data source reliability — 8 tools.

Enables AI coding agents to observe real-time Node, Vite, Next.js, Storybook, TypeScript, and browser runtime errors from a wrapped dev server, source-mapped to exact file, line, and column with the log lines preceding each crash. It exposes MCP tools for listing open errors, fetching full stack details, and checking or marking fixes as resolved, all locally with no code changes.

Gives AI assistants read-only access to a Kubernetes cluster's observability stack — Loki, Prometheus, Tempo, the Kubernetes API — plus AWS telemetry from CloudTrail, Config, ECR, and RDS. 23 tools for querying logs, metrics, traces, Kubernetes events, deployments, and audit history in plain language.

Enables mapping JavaScript error stack traces back to original source code, extracting context information to help developers locate and fix issues.

Enables engineering leaders to query their AI assistant for quality KPIs — MTTR, MTTA, DORA metrics, defect escape rate and SLA breaches — computed from Jira bug, incident and deployment CSV exports already on hand. It delivers trends, period comparisons, hotspot findings and ready-to-share executive summaries and HTML dashboards without a BI stack or data warehouse.