"QA review sentinel test marker" matching MCP servers:

Read-only MCP server for Kafka cluster health, consumer lag, partition state, and replay-readiness, enabling AI agents to diagnose streaming incidents without write access.

Hosted remote MCP server for issuing run receipts, summarizing agent changes, checking test evidence, flagging review risks, and exporting run logs for Antigravity agents.

Unified SIEM MCP gateway for AI-driven SOC operations and threat hunting across Azure Sentinel, Splunk, Wazuh, IBM QRadar, and Securonix.

Enables AI agents and software engineers to investigate and resolve realistic distributed-system incidents using safe MCP-based diagnostic tools for code, logs, metrics, traces, database, and deployments.

Enables AI assistants to query and analyze data in Azure Data Explorer, Log Analytics, and Microsoft Sentinel using Kusto Query Language (KQL) through tools, resources, and prompts.

Enables ingesting caller-supplied agent execution traces and comparing them against signed, versioned baselines of normal behaviour to surface silent drift. Reports severity with per-dimension attribution, a replayable exemplar episode, and visible suppression of declared maintenance windows or known change markers.

Enables an LLM assistant to analyze automated test results, search logs, group failures by cause, and draft Jira bugs with steps to reproduce, with dry-run Jira filing by default.

Enables agents to detect drift anomalies with CUSUM, forecast trends using Holt linear methods, and automatically trip a circuit breaker to protect workflows.

Turns Claude into an autonomous SOC analyst by ingesting security logs, detecting anomalies with ML, correlating events, mapping to MITRE ATT&CK, and generating incident reports.

A production-ready MCP server for SQL Server monitoring, diagnostics, and database operations, with native connectivity, session management, deadlock and blocking analysis, and health checks.

A self-hosted governance layer for MCP servers that enforces policies, audits tool calls, and manages approvals for AI agents.

Enables AI agents and SREs to diagnose Kubernetes incidents, perform root cause analysis, and generate safety-guardrailed GitOps remediation patches or kubectl commands. It supports live clusters, Alertmanager webhooks, and offline simulation scenarios.

Provides governed MCP tools for querying optionally restricted Microsoft Sentinel/Log Analytics tables and optional Defender XDR hunting data, retrieving incidents and entities, and—for agent identities only—adding attributed incident comments, with Entra ID authentication, KQL validation, rate limits, and redacted audit logging.

MCP server that coordinates autonomous infrastructure health monitoring agents, enabling natural-language telemetry queries and automated diagnosis, remediation, and verification.

Provides read-only access to a local FitBro environment, enabling queries of Postgres, retrieval of application and test logs, and on-demand Cucumber test runs via MCP.

An MCP filesystem telemetry server that watches directories and records every file change with SHA-256 hashes, enabling verification of edits through tools like recent_changes and query_events, with multi-project support and idle suspension.

Enables autonomous infrastructure health management by exposing tools for retrieving system logs, querying a knowledge base, executing SQL analytics, and simulating system commands, all integrated into an AI-driven incident response workflow.

A read-only IBM MQ diagnostic MCP server that safely provides AI agents with typed root-cause analysis and verified IBM documentation, while incorporating prompt-injection defense, OIDC+RBAC, and tamper-evident audit.

Uptime, SSL, DNS and domain monitoring you can talk to: check, create and manage monitors for all your client sites from Claude, ChatGPT, or any MCP client.

MCP server for managing Ubuntu servers over SSH. Enables Claude to check system health, inspect services, tail logs, review updates, and run commands remotely.

An MCP server that exposes a dbt project's run state as tools, enabling AI assistants to answer questions like 'is the warehouse healthy?' or 'what broke and why?' via plain English, using read-only access to dbt artifacts and warehouse data.

An MCP server that provides cost and reliability observability for LLM and agent workflows. It records model calls and allows querying and aggregating telemetry data through MCP tools.

Enables AI clients to assess infrastructure-as-code deployment risk, generate incident response runbooks, review CI/CD delivery readiness, and calculate SLO error budgets through structured advisory tools. Runs locally over stdio without cloud credentials or external API calls, returning guidance for platform work, pull request review, and production readiness checks.

An MCP server that exposes GPU-accelerated anomaly detection to AI assistants via the Model Context Protocol. Provides two MCP tools: waveguard_scan (send training + test data in one call, returns per-sample anomaly scores and top explanatory features) and waveguard_health (check API and GPU status). Works on time series, JSON, numbers, text, and images — fully stateless.

Enables analyzing coding-agent session transcripts to measure tool efficiency, detect loops, track test outcomes, and report costs, with MCP tools for listing sessions, analyzing sessions, finding loops, and generating cost reports.

Enables AI agents to build, test, debug, and interact with Kotlin Multiplatform Mobile (Android/iOS) applications through automated build pipelines, UI automation, crash analysis, and app state inspection.

Enables AI agents to monitor Docker containers, system resources, ports, and logs in real-time.

Checks what local coding agents such as Claude Code, Codex and Cursor really did: files changed, commands run and test results read from test output, not the agent's word. Unclear test results can be double-checked by Laya (on your computer) or TypeSafe's Jev (cloud, your own API key). Read-only.

A secure, local-first MCP server for read-only inspection and troubleshooting of development environments, exposing narrow, typed, auditable capabilities for repository inspection, log summarization, Docker review, and security scanning without granting unrestricted machine access.

Enables AI agents to manage Stape.io infrastructure, including container management, custom domains, power-ups, request logs, and Stape Store NoSQL database operations.