"Automating a QA End-to-End Workflow" matching MCP servers:

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

Provides observability for multi-agent workflows by tracking hierarchical task structure, architectural decisions, reasoning, encountered problems, code modifications with Git diffs, and temporal metrics.

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.

Fetches Langfuse observability traces directly into a VS Code coding agent's context, enabling querying and viewing trace data through natural language.

Read-only MCP server for TrueNAS Scale debugging, providing k3s tools for kubectl operations and whitelisted midclt calls for system info, apps, and pools.

MCP server that provides guarded, audited, read-only access to ops tooling (alerts, metrics, logs, deploys, runbooks) and a triage agent that diagnoses incidents end-to-end with CI-verified root cause analysis.

Enables intelligent troubleshooting, monitoring, and configuration of Cisco Meraki networks through natural language, with agentic workflows for automated diagnostics and health checks.

Enables AI agents to manage GPU training end-to-end through natural language, including submitting and scheduling jobs, monitoring logs and metrics, diagnosing failures, comparing runs, and recommending the best checkpoints.

An MCP server for debugging Temporal workflows, enabling LLM-assisted inspection of workflow executions, detailed workflow info, and event history.

MCP server that provides structured audit logging for AI agent repair tasks via tools to start, record, end, query, and export event traces, with JSONL persistence and SDK integration.

PiPeFlow passively tracks AI agent workflow states using a finite state machine, providing tools for declaring, advancing, and auditing pipelines with annotations and reports.

A thin MCP server wrapper that automatically audits all tool calls via Attestive's AuditClient, logging decisions and enabling verification of the hash chain. It provides an example server with audited tools and demonstrates end-to-end recording and verification through the MCP protocol.

Provides Claude AI assistants with focused monitoring tools for n8n workflow execution analysis, including active workflow listing, execution history with KPIs, and detailed failure information.

A lightweight MCP server that enables AI assistants to deploy, inspect, and operate Kubernetes workloads through high-level workflow tools, reducing token usage with structured outputs.

Connects AI assistants to New Relic with read-only access to NRQL, logs, metrics, traces, alerts, and more. Offers optional, gated write operations with a dry-run and confirmation workflow.

An enterprise-level MCP gateway and proxy that sits between an organization's MCP servers and clients. MCP Manager mitigates security threats, enables fine-grained permissions, enforces policies and guardrails, and generates comprehensive, end-to-end logs.

Enables AI assistants to interact with DataDog's observability platform through a standardized interface. Supports monitoring infrastructure, managing events, analyzing logs and metrics, and automating operations like alerts and downtimes.

A Model Context Protocol server that connects AI agents to IBM Concert, enabling autonomous workflow health monitoring, incident diagnosis, auto-remediation, CVE triage, and Slack alerting through natural language.

A middleware service that uses Model Context Protocol to analyze and automate Zabbix events with AI, enabling automated incident response and workflow automation through n8n integration.

A FastMCP server that provides DataDog log search and monitoring with service-aware filtering, preview-execute workflow, and response size safeguards.