Sending Traces

Mibo accepts traces on a single endpoint, POST /public/traces, with two supported request shapes. Both produce the same canonical trace internally — pick whichever fits your stack.

The two paths

OpenTelemetry (OTLP)Point any OTel exporter at Mibo. Use this if you already emit OTel spans, use n8n's native OTLP export, or run Flowise self-hosted with native OTel enabled.

Your APIPOST the canonical {spans:[...]} JSON directly. Use this from curl, the n8n community node, the Flowise Your API template, or any stack on a managed host with no host-level OTel.

Both paths are first-class. Neither is a workaround for the other.

Which one fits your stack

You’re on…	Use
A service emitting OTel via the Vercel AI SDK, OpenLLMetry, or another GenAI instrumentation	OTLP. See the Vercel AI SDK and OpenLLMetry quickstarts.
LangChain or LangGraph agents	OTLP through OpenLLMetry, which instruments LangChain
An OpenTelemetry Collector that already exports to another backend	OTLP. Add Mibo as a second exporter. See Collector fan-out.
n8n self-hosted ≥ 2.19 using n8n’s native OTLP export (Preview)	OTLP. Node content is not exported, so evaluation is mostly structural. See Send traces from n8n.
n8n that needs node input and output, including n8n Cloud	Your API through the n8n community node
Flowise self-hosted with native OTel enabled	OTLP
Flowise Cloud (no host-level OTel)	Your API via the Flowise template
Your own code without OpenTelemetry, scripts, or curl	Your API

If you can choose OTLP, it usually wins — your existing exporter is already batched, retried, and instrumented. Your API exists so users on managed hosts (n8n Cloud, Flowise Cloud, anything where you can’t touch host env vars) get the same first-class trace ingestion.

What’s the same across both paths

Endpoint: POST https://api.mibo-ai.com/public/traces
Auth: x-api-key header. See API Keys & Trace Routing.
Identity: Your API uses the x-request-id HTTP header. Present → replaces the trace with that id. Absent → server-generated UUID, so each POST creates a new trace. OTLP uses traceId to merge batches and ignores x-request-id.
Agent resolution: Your API uses a single-agent key automatically; otherwise it requires platformId (top level) or metadata.mibo.platform_id. OTLP routes single-Agent keys directly. Other keys match service.name within their allowed Agents. A key for all agents in the workspace can fall back to its only active non-demo Agent when the service name is unconfigured.
Canonical span model: spans with span_id, parent_span_id, name, attributes, optional timing and status. span.name is always the user-facing display label of the step.
Redaction: Mibo always redacts secrets before it stores a trace. Personal data redaction is an opt-in workspace setting. See Data handling.

What’s different

	OTLP	Your API
Body shape	`resourceSpans[].scopeSpans[].spans[]` (OTel envelope)	`{ spans: [...] }` (flat)
Attributes encoding	OTel key/value list (`{ key, value: { stringValue: "..." } }`)	Plain JSON object
Batching	Multi-POST: server merges by `traceId`/`span_id`	One POST per trace; create-or-replace by `externalId`
Best for	Long-lived processes, SDK-instrumented services	Synchronous flows, short scripts, managed-host integrations

Mibo reads the same attributes on both paths — gen_ai.response.text, gen_ai.usage.input_tokens, gen_ai.tool.name, http.response.status_code, and the rest of the GenAI / HTTP semconv keys. Your assertions don’t change.

What every span should carry

Whichever path you send on, these are the attributes assertions look up. Emit what you have; missing data surfaces as missing instrumentation in the dashboard rather than silent pass/fail.

Attribute	What it powers
`gen_ai.response.text`	Semantic assertions, `response_regex`, default text extraction
`gen_ai.output.messages`	Same as above when present (preferred over `response.text`)
`gen_ai.usage.input_tokens` / `output_tokens` / `reasoning.output_tokens`	`token_limit`
`gen_ai.tool.name` + `gen_ai.tool.call.arguments`	`tool_call` (the span becomes a child tool call of its parent)
`http.response.status_code`	`http_status`
Span `name`	`node_call` (case-insensitive substring match)
Root span `start/end_time_unix_nano`	`response_time.max_ms`

See Assertion Reference for the full mapping.

Next steps

OTLP deep-diveExporter envs, n8n / Flowise self-hosted recipes, batching.

Your API deep-diveCanonical {spans:[...]} body, headers, examples.

n8nNative OTLP export, community node, and HTTP Request node options for n8n.

Flowise templateImportable Custom JS Function for any Flowise chatflow.