| name | api-telemetry |
| description | Catalog of OpenTelemetry instrumentation built into framework `@cyanheads/mcp-ts-core` — spans, metrics, completion logs, env config, runtime caveats, custom instrumentation patterns, and cardinality rules. Use when enabling OTel export, adding custom spans or metrics in services, debugging missing telemetry, looking up attribute names, or deciding what's safe to put on a metric attribute vs. a span.
|
| metadata | {"author":"cyanheads","version":"1.0","audience":"external","type":"reference"} |
Overview
The framework auto-instruments every tool, resource, prompt, storage, LLM, speech, and graph call — each gets its own span and the standard counters/histograms. HTTP server requests pick up spans from HttpInstrumentation (or @hono/otel on the HTTP transport). Auth checks, session lifecycle, and task lifecycle are tracked as metrics only — auth decorates the active HTTP span with attributes, sessions and tasks emit counters.
requestId, traceId, and tenantId correlate automatically across spans, metrics, and logs. Pino logs get trace_id/span_id injected when a span is active.
For the helper API surface (withSpan, createCounter, createHistogram, buildTraceparent, etc.) — see the api-utils skill, Telemetry section. This skill is the catalog of what is emitted; that one is the reference for how to emit your own.
Enabling export
OTel is off by default. OTEL_ENABLED=true alone does nothing — you also need an OTLP endpoint. Without an endpoint the SDK is configured but nothing leaves the process.
| Env var | Default | Purpose |
|---|
OTEL_ENABLED | false | Master switch. Must be true to start the SDK. |
OTEL_EXPORTER_OTLP_TRACES_ENDPOINT | — | OTLP/HTTP traces endpoint (e.g. http://localhost:4318/v1/traces). |
OTEL_EXPORTER_OTLP_METRICS_ENDPOINT | — | OTLP/HTTP metrics endpoint (e.g. http://localhost:4318/v1/metrics). |
OTEL_SERVICE_NAME | package.json name | service.name resource attribute. |
OTEL_SERVICE_VERSION | package.json version | service.version resource attribute. |
OTEL_TRACES_SAMPLER_ARG | 1.0 | Trace sampling ratio (0–1) for TraceIdRatioBasedSampler. |
OTEL_LOG_LEVEL | INFO | OTel diagnostic logger level (NONE/ERROR/WARN/INFO/DEBUG/VERBOSE/ALL). |
Metrics push via PeriodicExportingMetricReader every 15 seconds. Traces use BatchSpanProcessor.
Runtime support
| Runtime | Behavior |
|---|
| Node.js / Bun | Full NodeSDK. Auto-instrumentations: HTTP server (Node http hooks; skips /healthz), Pino logs (trace_id/span_id injection). On the HTTP transport, when OTel is enabled and @hono/otel is installed, httpInstrumentationMiddleware is also wired onto the MCP endpoint — fills the gap on Bun, where the Node http auto-instrumentation silently no-ops. Manual spans, custom metrics, and OTLP export work on Bun regardless. |
| Cloudflare Workers / V8 isolates | NodeSDK is unavailable. SDK init no-ops silently. createCounter/createHistogram/withSpan calls still work via the global OTel API but produce no output unless you wire a Worker-compatible exporter and ctx.waitUntil() for flush. |
Cloud platform detection auto-populates resource attributes:
| Detected | Attributes set |
|---|
| Cloudflare Workers | cloud.provider=cloudflare, cloud.platform=cloudflare_workers |
| AWS Lambda | cloud.provider=aws, cloud.platform=aws_lambda, cloud.region from AWS_REGION |
| GCP Cloud Run / Functions | cloud.provider=gcp, cloud.platform=gcp_cloud_run (or gcp_cloud_functions), cloud.region from GCP_REGION |
| All | deployment.environment.name from config.environment |
Spans
Every handler call gets a span. Nested operations (storage, graph, LLM) become child spans on the same trace. All spans carry code.function.name and code.namespace for code-attribution. Errors are recorded via span.recordException() and SpanStatusCode.ERROR; McpError codes surface as the *.error_code attribute.
| Span name | Source | Key attributes |
|---|
tool_execution:<tool> | every tool call | mcp.tool.input_bytes, mcp.tool.output_bytes, mcp.tool.duration_ms, mcp.tool.success, mcp.tool.error_code, mcp.tool.partial_success, mcp.tool.batch.{succeeded,failed}_count |
resource_read:<resource> | every resource handler | mcp.resource.uri, mcp.resource.mime_type, mcp.resource.size_bytes, mcp.resource.duration_ms, mcp.resource.success, mcp.resource.error_code |
prompt_generation:<prompt> | every prompt handler | mcp.prompt.input_bytes, mcp.prompt.output_bytes, mcp.prompt.message_count, mcp.prompt.duration_ms, mcp.prompt.success, mcp.prompt.error_code |
storage:<op> | StorageService (every call) | mcp.storage.operation, mcp.storage.duration_ms, mcp.storage.success, mcp.storage.key_count (batch ops) |
graph:<op> | GraphService (every call) | mcp.graph.operation, mcp.graph.duration_ms, mcp.graph.success |
gen_ai.chat_completion | OpenRouter LLM provider | gen_ai.system=openrouter, gen_ai.request.model, gen_ai.request.{max_tokens,temperature,top_p,streaming}, gen_ai.response.model, gen_ai.usage.{input,output,total}_tokens |
speech:tts | ElevenLabs provider | mcp.speech.provider, mcp.speech.operation, mcp.speech.input_bytes, mcp.speech.output_bytes, mcp.speech.duration_ms, mcp.speech.success |
speech:stt | Whisper provider | same as speech:tts |
Trace context propagates across boundaries via W3C traceparent headers. See api-utils → telemetry/trace for withSpan, buildTraceparent, extractTraceparent, createContextWithParentTrace, injectCurrentContextInto, runInContext signatures.
Metrics
All custom metrics are namespaced mcp.* (or process.* / http.client.* where standard semconv applies). Lazy-initialized on first emission; the universal ones are eagerly created at startup so series exist from the first export cycle.
Tools, resources, prompts
| Metric | Type | Unit | Attributes |
|---|
mcp.tool.calls | counter | {calls} | mcp.tool.name, mcp.tool.success |
mcp.tool.duration | histogram | ms | mcp.tool.name, mcp.tool.success |
mcp.tool.errors | counter | {errors} | mcp.tool.name, mcp.tool.error_category (upstream/server/client) |
mcp.tool.input_bytes | histogram | bytes | mcp.tool.name |
mcp.tool.output_bytes | histogram | bytes | mcp.tool.name |
mcp.tool.param.usage | counter | {uses} | mcp.tool.name, mcp.tool.param (top-level keys supplied by caller) |
mcp.resource.reads | counter | {reads} | mcp.resource.name, mcp.resource.success |
mcp.resource.duration | histogram | ms | mcp.resource.name, mcp.resource.success |
mcp.resource.errors | counter | {errors} | mcp.resource.name |
mcp.resource.output_bytes | histogram | bytes | mcp.resource.name |
mcp.prompt.generations | counter | {generations} | mcp.prompt.name, mcp.prompt.success |
mcp.prompt.duration | histogram | ms | mcp.prompt.name, mcp.prompt.success |
mcp.prompt.errors | counter | {errors} | mcp.prompt.name, mcp.prompt.error_category |
mcp.prompt.input_bytes | histogram | bytes | mcp.prompt.name |
mcp.prompt.output_bytes | histogram | bytes | mcp.prompt.name |
mcp.prompt.message_count | histogram | {messages} | mcp.prompt.name |
mcp.requests.active | up/down counter | {requests} | — (in-flight handler executions, all three types) |
Storage, LLM, speech, graph
| Metric | Type | Unit | Attributes |
|---|
mcp.storage.operations | counter | {ops} | mcp.storage.operation, mcp.storage.success |
mcp.storage.duration | histogram | ms | mcp.storage.operation, mcp.storage.success |
mcp.storage.errors | counter | {errors} | mcp.storage.operation |
mcp.llm.requests | counter | {requests} | gen_ai.system, gen_ai.request.model |
mcp.llm.duration | histogram | ms | gen_ai.system, gen_ai.request.model |
mcp.llm.errors | counter | {errors} | gen_ai.system, gen_ai.request.model |
mcp.llm.tokens | counter | {tokens} | gen_ai.request.model, gen_ai.token.type (input/output) |
mcp.speech.operations | counter | {ops} | mcp.speech.operation (tts/stt), mcp.speech.provider, mcp.speech.success |
mcp.speech.duration | histogram | ms | mcp.speech.operation, mcp.speech.provider |
mcp.speech.errors | counter | {errors} | mcp.speech.operation, mcp.speech.provider |
mcp.graph.operations | counter | {ops} | mcp.graph.operation, mcp.graph.success |
mcp.graph.duration | histogram | ms | mcp.graph.operation, mcp.graph.success |
mcp.graph.errors | counter | {errors} | mcp.graph.operation |
Transport, auth, sessions, tasks
| Metric | Type | Unit | Attributes |
|---|
mcp.auth.attempts | counter | {attempts} | mcp.auth.outcome (success/failure/missing), mcp.auth.failure_reason |
mcp.auth.duration | histogram | ms | mcp.auth.outcome, mcp.auth.failure_reason |
mcp.sessions.events | counter | {events} | mcp.session.event (created/terminated/rejected/stale_cleanup) |
mcp.session.duration | histogram | s | — |
mcp.sessions.active | observable gauge | {sessions} | — |
mcp.heartbeat.failures | counter | {failures} | mcp.connection.transport (stdio/http) |
mcp.http.close_failures | counter | {failures} | surface (transport/server), trigger (success/error/sse-abort) — per-request close threw or timed out |
mcp.http.per_request.created | counter | {instances} | kind (server/transport) — per-request McpServer and McpSessionTransport instances created |
mcp.http.per_request.finalized | counter | {instances} | kind (server/transport) — per-request instances reclaimed by GC; persistent gap vs created indicates a leak |
mcp.tasks.created | counter | {tasks} | mcp.task.store_type (in-memory/storage) |
mcp.tasks.status_changes | counter | {transitions} | mcp.task.status, mcp.task.store_type |
mcp.tasks.active | observable gauge | {tasks} | — (in-memory store only) |
Errors, rate limits, HTTP client
| Metric | Type | Unit | Attributes |
|---|
mcp.errors.classified | counter | {errors} | mcp.error.classified_code (JSON-RPC code), operation |
mcp.ratelimit.rejections | counter | {rejections} | mcp.rate_limit.key |
http.client.request.duration | histogram | s | http.request.method, server.address, http.response.status_code (when > 0; absent on network errors before a response is received) |
Process
Auto-registered when process.memoryUsage / process.uptime / perf_hooks are available (Node/Bun, not Workers). The three memory gauges share a single process.memoryUsage() snapshot per collection cycle, refreshed at most every 100 ms.
| Metric | Type | Unit | Notes |
|---|
process.memory.rss | observable gauge | bytes | Resident set size |
process.memory.heap_used | observable gauge | bytes | V8 heap used |
process.memory.heap_total | observable gauge | bytes | V8 total heap |
process.uptime | observable gauge | s | Process uptime |
process.event_loop.delay | observable gauge | ms | p99 delay (monitorEventLoopDelay resolution=20) |
process.event_loop.utilization | observable gauge | 1 | 0 = idle, 1 = saturated |
Logs
Pino logs are auto-instrumented by @opentelemetry/instrumentation-pino. When a span is active, trace_id and span_id are injected into the record. Combined with the framework logger's automatic requestId/tenantId correlation, every log line is searchable by trace.
For domain logging inside handlers, use ctx.log (debug/info/notice/warning/error) — auto-includes requestId, traceId, tenantId, spanId. The completion log emitted at the end of every handler carries a metrics payload, with fields tuned to each surface:
| Handler | Log message | metrics fields |
|---|
| Tool | Tool execution finished. | durationMs, isSuccess, errorCode, inputBytes, outputBytes, plus partialSuccess / batchSucceeded / batchFailed when the result is a partial-success batch |
| Resource | Resource read finished. | durationMs, isSuccess, errorCode, outputBytes, uri, mimeType |
| Prompt | Prompt generation finished. (or failed.) | durationMs, isSuccess, errorCode, inputBytes, outputBytes, messageCount |
Custom instrumentation
Need a span or metric for your own service? Use the helpers from @cyanheads/mcp-ts-core/utils (full signatures in api-utils → Telemetry):
import { withSpan, createCounter, createHistogram } from '@cyanheads/mcp-ts-core/utils';
const myOps = createCounter('myservice.operations', 'My service ops', '{ops}');
const myDuration = createHistogram('myservice.duration', 'My service duration', 'ms');
export async function doWork() {
return withSpan('myservice.do_work', async (span) => {
const t0 = performance.now();
try {
const result = await reallyDoWork();
span.setAttribute('myservice.items', result.length);
return result;
} finally {
myDuration.record(performance.now() - t0);
myOps.add(1);
}
}, { 'myservice.region': 'us-west' });
}
Span context propagates automatically — withSpan calls inside a tool_execution:* span appear as children. runInContext(ctx, fn) carries the active OTel context across async boundaries (setTimeout, queueMicrotask).
For attribute keys, prefer the ATTR_* constants exported from @cyanheads/mcp-ts-core/utils (telemetry/attributes) over hand-typed strings — keeps you in step with framework conventions and avoids typos. Standard OTel semantic conventions (HTTP, cloud, service, network, etc.) are NOT re-exported — import those directly from @opentelemetry/semantic-conventions.
Visualization
An example Grafana dashboard JSON and vendor-agnostic query recipes (Prometheus, Datadog, New Relic, Honeycomb) live at docs/telemetry/ in the framework source — not bundled in the npm package, so consult the GitHub repo.
Cardinality discipline
Series are cheap to emit but expensive to store and query. The framework deliberately keeps high-cardinality identifiers off metric attributes and on spans only. Follow the same rule when adding your own metrics.
| On metrics | On spans / logs only |
|---|
mcp.resource.name (URI template) | mcp.resource.uri (full URI with IDs) |
gen_ai.request.model (bounded enum) | mcp.tenant.id, mcp.client.id, mcp.auth.subject |
| Bounded enum / template strings | Per-request unique IDs, free-form user input, opaque tokens |
When in doubt: if the attribute can take more than ~100 distinct values across a fleet's runtime, it belongs on the span, not the metric.
