Connects AI assistants to Warpmetrics telemetry data to monitor AI agent performance, execution runs, and LLM costs. It allows users to query success rates, latency, and spend metrics directly through natural language interfaces.
Enables agents to query real-time and historical metrics for locally served Ollama and vLLM instances, including request rates, latency, token counts, and GPU utilization, over stdio.
Enables AI assistants to interact with Datadog's observability platform via natural language, covering metrics, logs, APM, monitors, dashboards, incidents, and infrastructure.
Lets AI agents query, manage, and operate their LLM observability data directly from the conversation. Provides 87 tools for cost analysis, alerting, anomaly detection, and runtime control gates.
Enables AI agents to analyze text and retrieve real-time system metrics such as CPU, memory, and uptime through LangChain tool calling, with an embedded web UI for testing queries and viewing tool execution logs.
