A paid remote MCP for tracking AI agent execution and debugging failures in production. It exposes five tools: record_agent_run for logging executions, detect_agent_failure for automated failure detection, replay_tool_call_incident to reconstruct what happened during an error, issue_sla_receipt for compliance documentation, and export_client_status for reporting. You authenticate with a bearer token from their website, then connect via Streamable HTTP. Reach for this when you need centralized monitoring across multiple agent deployments, want incident replay without building your own tooling, or need audit trails and SLA documentation for client-facing agent systems. Not open source, just hosted infrastructure with a JSON-RPC interface.
Track agent runs, failures, replay evidence, and SLA receipts from one MCP.
Paid remote MCP for AI agent run monitoring, failure detection, tool-call incident replay, SLA receipts, and client status exports.
com.clauxel.agentmonitorrelay/agentmonitorrelay-mcpThis is a paid hosted remote MCP. Production calls require a bearer token issued from the product website.
Authorization: Bearer <token>
Unauthenticated browser visits to /mcp return a clear JSON error instead of internal details.
record_agent_rundetect_agent_failurereplay_tool_call_incidentissue_sla_receiptexport_client_statusThis repository is a public documentation and directory-submission reference for the hosted service. It does not contain the private production source code.
io.github.ericm1018/skillfm-llm-cost-optimizer-openai-anthropic-usage
io.github.mikerawsonnz/llm-orchestration-agent
io.github.mikerawsonnz/authenticated-llm-agent
labforgedev/copilot-memory-mcp
csoai-org/agent-prompt-injection-firewall-mcp
io.github.mikerawsonnz/authenticated-multi-llm-agent