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"How to Create Workflows in n8n" matching MCP servers:

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    Enables LLMs to analyze and manage DBOS workflows, including introspection, workflow management, and authentication, to help debug applications in development or production.
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    MIT
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    An MCP server for detecting retry loops and analyzing iteration patterns in agentic coding workflows, providing structured debugging intelligence to improve repair attempts.
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    MIT
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    Enables AI assistants to interact with Healthchecks.io, allowing users to list, create, update, pause, resume, and delete checks, as well as view ping history and integrations.
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    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.
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    Operates Rancher-managed Kubernetes through any MCP client with capability detection, generic resource access, and curated workflows, wrapped in an audit-logged, rate-limited, confirmation-guarded safety model.
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    Enables interaction with Incident.io to manage incidents, severities, and health checks via natural language. Provides endpoints for getting and creating incidents.
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    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.
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    Logpoint MCP Server provides MCP endpoints for Logpoint SIEM, enabling search, incident management, alert rules, and integrations with n8n and Claude for SIEM operations.
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    Provides observability for multi-agent workflows by tracking hierarchical task structure, architectural decisions, reasoning, encountered problems, code modifications with Git diffs, and temporal metrics.
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    Real-time observability dashboard for monitoring AI agents in multi-agent development workflows, with live WebSocket updates of tool calls, sessions, and usage statistics.
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    Radar is an open-source Kubernetes observability and diagnostics MCP server. It exposes cluster health, workload diagnosis, logs, events, topology, audit findings, and remediation actions to AI agents through the Model Context Protocol.
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    Apache 2.0
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    Exposes homelab and IT-ops tools to Claude, including system health monitoring, Grafana alert states, Docker container status, Loki logs, SMART disk health, and more.
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    An MCP server that provides monitoring tools for Codex agents, allowing them to create and wait on conditions using commands, log files, file events, and custom probes, replacing polling loops with event-driven blocking.
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    MIT
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    MCP server for Drumbeats monitoring. Enables creating monitors, triaging incidents, and running HTTP/SSL/DNS checks using natural language from any AI client.
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    A Model Context Protocol server that gives LLM clients full access to your AppDynamics monitoring data — plus the ability to create and manage dashboards and health rules.
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    MCP server that enables querying an OpenObserve instance for logs, traces, and metrics via tools like search_logs, search_traces, get_trace, and query_metrics, supporting natural-language-driven observability workflows.
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    MIT
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    eBPF-based GPU causal observability agent with MCP server. Traces CUDA Runtime and Driver APIs via kernel uprobes and host events via tracepoints to build causal chains explaining GPU latency. 7 tools: get_check, get_trace_stats, get_causal_chains, get_stacks, run_demo, get_test_report, run_sql. Telegraphic compression reduces token usage ~60%. Supports stdio and HTTPS (TLS 1.3) transport.
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