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Know exactly what your agents did

Autonomous systems calling real APIs need better than 'it worked on my machine'. Every invocation through the gateway is traced, attributable to a named key, and replayable.

call log: support-bot
TIME      TOOL                              KEY           LAT    STATUS
12:04:31  zendesk.ticket.search             support-bot   187ms  ok
12:04:32  zendesk.ticket.read               support-bot    94ms  ok
12:04:34  shopify.order.get                 support-bot   210ms  ok
12:04:36  stripe.refund.create              support-bot     -    denied  ← out of scope
12:04:36  slack.message.post                support-bot    92ms  ok
12:05:02  zendesk.ticket.update             support-bot   134ms  ok
12:05:19  snowflake.query.run               analytics-bot 1.8s   ok      truncated 41KB→4KB
12:05:44  salesforce.opportunity.search     revops-bot     -     error   upstream 503, retried 2×
What you get

Four questions you can finally answer

These are the ones that come up the first time an agent does something surprising in production.

What did it call?

A chronological trace of every tool invocation with arguments, filterable by agent, key, connector, tool or outcome.

Why was it slow?

Gateway overhead and upstream latency are reported separately, so you can tell a slow API from a slow agent.

What was blocked?

Denied calls are logged as loudly as successful ones. An out-of-scope attempt is a signal worth seeing.

Can I reproduce it?

Replay any logged call with the same arguments to separate an agent bug from an upstream failure.

Export

It does not have to live in our dashboard

Traces are OpenTelemetry-shaped and logs stream out, so agent activity lands next to the rest of your telemetry.

OpenTelemetry traces

Spans per tool call with gateway and upstream timing, exported to any OTLP collector.

Log streaming

Structured JSON to Datadog, S3, or an HTTPS endpoint you control.

SIEM export

Audit-grade records with configurable retention for compliance review.

Usage metering

Per-key, per-connector call counts and error rates for cost attribution.

FAQ

Observability questions

What is captured for each call?

Timestamp, calling key and agent label, connector and tool, input arguments, upstream status, gateway and upstream latency, response size, and whether the response was truncated or cached.

Are arguments stored in full?

By default arguments are stored with configurable redaction rules for fields you mark sensitive. You can also disable argument capture entirely per connector while keeping the rest of the trace.

Can I replay a call?

Yes. Any logged call can be re-issued from the dashboard against the same connector with the same arguments, which is usually the fastest way to tell an agent bug from an upstream one.

Does this integrate with our existing tooling?

Traces export in OpenTelemetry format, and logs stream to Datadog, S3 or an HTTPS endpoint. Enterprise plans add direct SIEM connectors and configurable retention.

Give every agent one endpoint

Connect your apps once, mint a scoped key, and point Claude, Codex, Cursor or your own runtime at a single MCP server.

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