An AI-native incident response server that exposes diagnostic tools (system status, error logs, ticket creation) via MCP, enabling LLM agents to autonomously assess and respond to incidents.
MCP server for autonomous MLOps incident response, enabling drift detection, deployment history analysis, and human-approved rollback execution via gated tools.
An MCP server that enables autonomous self-healing AIOps by monitoring system metrics and executing dynamic remediation through LLM-driven tool routing, with support for Streamlit UI and CLI.
Python-based MCP server for full-cycle incident management, enabling detection, root-cause analysis, and response guidance through tools like detect_incidents, analyze_incident, and suggest_response.
MCP server that enables AI agents to run a deterministic orchestration loop with decomposition, subagent execution, and review feedback across multiple LLM backends.
MCP server that connects LLMs to Kubernetes clusters for troubleshooting, scanning failing pods, diagnosing root causes, and applying guarded fixes or generating manifests via natural language.