telemetry.dev documentation
Send your first AI trace, then connect the provider, framework, or coding agent you already use.
telemetry.dev records what your AI application does. Each run becomes one trace that shows every model call, tool call, and step in order, with the tokens, cost, latency, and errors of each one.

telemetry.dev is built on OpenTelemetry. The SDKs send standard OTLP/HTTP, and so can the OpenTelemetry setup you already run.
Get started
Quickstart
Send a real trace and find it in your project in about five minutes.
How it works
Traces, spans, environments, and what the ingest service does with your data.
Connect your application
Model provider or framework
Wrap the OpenAI, Anthropic, Gemini, or Bedrock client, or add tracing to the Vercel AI SDK, LangChain, and other frameworks.
Coding agent
Record Claude Code, Cursor, opencode, and other agents on your machine.
TypeScript SDK
Record functions, model calls, tools, and agents on Node.js, Vercel Edge, or Cloudflare Workers.
Python SDK
Record synchronous and asynchronous Python code with a decorator or context managers.
Existing OpenTelemetry
Keep your instrumentation and add telemetry.dev as an OTLP/HTTP destination.
What you can do
- Debug a single run. Open a trace to read each model call’s input and output, each tool’s arguments and result, and the error that ended a failed run.
- Follow a conversation. Traces that share a session ID are grouped into one session.
- Track cost and usage. Tokens and cost are calculated per span and added up per trace, model, user, and environment.
- Keep sensitive data out. Turn off prompt and response capture per environment, and redact secrets and personal data before storage.
Platform
Traces, sessions, and logs
Search traces, read the span waterfall, and follow sessions.
Analytics
Requests, cost, p95 latency, tokens, and error rate over time.
Privacy and retention
Control what is captured, redact sensitive values, and set retention.
OTLP ingest API
Endpoints, authentication, limits, and error responses.