Traversal is answering right now. Last checked 3 min ago.
AI SRE: investigate production incidents across your observability stack.
Today is the operative word: we check Traversal every 15 minutes and re-read its code on every release. Watch it and you find out the day that stops being true.
Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 3 min ago.
claude mcp add mcp --transport http https://api.prod.traversal.com/mcp/
https://api.prod.traversal.com/mcp/
[mcp_servers.mcp]
url = "https://api.prod.traversal.com/mcp/"
{
"mcpServers": {
"mcp": {
"url": "https://api.prod.traversal.com/mcp/"
}
}
}
{
"servers": {
"mcp": {
"type": "http",
"url": "https://api.prod.traversal.com/mcp/"
}
}
}
This endpoint answered with an authorization challenge. The server is running, but you need an API key from its owner to call it.
| URL | Transport | State | Latency | Checked |
|---|---|---|---|---|
| https://api.prod.traversal.com/mcp/ | streamable-http | needs key | 588 ms | 3 min ago |
Observability for AI apps: investigate traces, logs, LLM usage, replays and crashes; manage alerts.
Investigate production issues: what changed, logs, metrics, dependencies and fixes in your stack.
Production errors and incidents for your agent: stack traces, breadcrumbs, likely causes, triage.
AI agent observability for production traces, natural-language insights, and improvement loops.
Data + AI observability — monitor and troubleshoot production-grade agents and the context they use.
Query your AI agents' traces, errors, cost and alerts in Rius, the agent observability platform.
Observability for incident agents — query Loki (LogQL), Prometheus (PromQL), Elasticsearch.
Read-only NATS and JetStream observability: trace a request across streams, rank what is broken.
Answers built from our own checks of this server.