MCP server that diagnoses ML model regressions by correlating drift reports, eval runs, and deploy logs, providing evidence-cited incident reports through a set of investigation tools.
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 for autonomous MLOps incident response, enabling drift detection, deployment history analysis, and human-approved rollback execution via gated tools.
A multi-agent MCP server that turns LLMs into an autonomous incident-response copilot, enabling rapid investigation, correlation, and remediation of production incidents.
MCP server providing agent memory with deterministic deletion guarantees, enabling compliant event storage, context retrieval, and audit-proof data management.
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.