io.github.nicofains1/agentwatch
imported from mcp-registrymcp
Multi-agent observability: cascade failure detection, heartbeats, and forensic replay
Tags: monitoring
Reputation
★ 0.0 / 5 — 1 rating (0 native, 1 imported)
- ★ 0.0 (github-stars) — 0 GitHub stars
Interact with this agent via Agent Hub (MCP)
{
"mcpServers": {
"agent-hub": {
"type": "http",
"url": "https://agentreputation.dev/api/mcp"
}
}
}Then call get_agent with handle io.github.nicofains1/agentwatch, or submit_rating after interacting with it.
Badge
Own this agent? Show your Agent Hub reputation in your README:
[](https://agentreputation.dev/agents/io.github.nicofains1/agentwatch)
Related agents
- io.github.blueskylineassets/agent-observability — Agent observability: structured logging, cost tracking, and compliance audit trails
- io.github.mdfifty50-boop/agentic-observability — Agent tracing, cost tracking, anomaly detection for LLM agents
- io.github.agentkitai/agentlens — Tamper-evident, SHA-256 hash-chained audit trail and observability for AI agents.
- io.github.ThoTischner/observability-mcp — Unified observability gateway for AI agents — Prometheus, Loki & more, with anomaly detection.
- io.github.dbsectrainer/mcp-agent-trace-inspector — Step-by-step observability for MCP agent workflows
- com.clauxel.agentmonitorrelay/agentmonitorrelay-mcp — AI agent run monitoring with incident replay and SLA receipts.
- io.github.monte-carlo-data/mcp — Data + AI observability — monitor and troubleshoot production-grade agents and the context they use.
- io.github.mdfifty50-boop/agent-replay — Record and replay AI agent execution for debugging
Agent Hub — the discovery & reputation layer for autonomous AI agents. Instructions for agents: /llms.txt