telemetry.dev shows each run of your AI agent as one trace. Each model call and tool call is a span with its duration, tokens, cost, and error. Prompts and evals use the same traces: change a prompt without a deploy, then run it on a dataset and compare the scores with production. Alerts tell you about errors, cost spikes, and agent loops. Connect with our TypeScript or Python SDK, or with the OpenTelemetry exporter that you already use.
Hi Product Hunt, I'm Ephraim, one of the makers of telemetry.dev.
When an agent breaks in production, you want to know which step did it and what the run cost. telemetry.dev shows each run as one trace, with every model call and tool call as a span with its tokens, cost, and error.
New in this launch:
- Prompt management: change prompts without a deploy
- Evals: test a new prompt version on a dataset before it goes live
- Alerts when errors pile up or a run gets expensive
- A CLI and an MCP server, so your coding agent can read your traces
It's built on OpenTelemetry, with TypeScript and Python SDKs for OpenAI, Anthropic, the Vercel AI SDK, LangChain and more. The free plan needs no card, and the code PHBU7A47FH gets you 1 month of Pro.
What's the hardest part of debugging your agents right now?
Congrats on the launch! I love how each run shows up as one trace — is cost or errors usually the first thing you check in a trace?
Being able to track AI costs and errors in one place seems super helpful, especially for businesses trying to work more efficiently
The MCP server part is what caught my eye — when a coding agent reads a trace to fix a failing run, does it see the full prompt and tool inputs, or can you redact sensitive parts first? I'm wondering how you keep debugging useful without leaking things like API keys or user data into the agent's context.
Congrats Ephraim. We run a remote MCP server, so the agent loop lives in the user’s Claude, not on our side. All we see are separate tool calls coming in. Can telemetry.dev group the calls from one conversation into a single trace from the server side, or does it have to sit inside the agent?
Impressive tracing. Questions: does pricing scale for high-volume inference? Self-hosting option? How does this compare to vanilla OpenTelemetry sampling?
ive built ai apps and always felt I needed something like this to debug and improve my ai responses. dope launch
Swapping a prompt without deploying and scoring it against the same traces that came from production is the loop I have been faking with spreadsheets, and alerting on agent loops alone would pay for itself.
About telemetry.dev on Product Hunt
“LLM observability for AI agents”
telemetry.dev launched on Product Hunt on October 31st, 2026 and earned 201 upvotes and 18 comments, earning #3 Product of the Day. telemetry.dev shows each run of your AI agent as one trace. Each model call and tool call is a span with its duration, tokens, cost, and error. Prompts and evals use the same traces: change a prompt without a deploy, then run it on a dataset and compare the scores with production. Alerts tell you about errors, cost spikes, and agent loops. Connect with our TypeScript or Python SDK, or with the OpenTelemetry exporter that you already use.
telemetry.dev was featured in Analytics (174.3k followers), Developer Tools (522.2k followers) and Artificial Intelligence (482.5k followers) on Product Hunt. Together, these topics include over 242.6k products, making this a competitive space to launch in.
Who hunted telemetry.dev?
telemetry.dev was hunted by fmerian. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how telemetry.dev stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
fmerian
Hi Product Hunt, I'm Ephraim, one of the makers of telemetry.dev.
When an agent breaks in production, you want to know which step did it and what the run cost. telemetry.dev shows each run as one trace, with every model call and tool call as a span with its tokens, cost, and error.
New in this launch:
- Prompt management: change prompts without a deploy
- Evals: test a new prompt version on a dataset before it goes live
- Alerts when errors pile up or a run gets expensive
- A CLI and an MCP server, so your coding agent can read your traces
It's built on OpenTelemetry, with TypeScript and Python SDKs for OpenAI, Anthropic, the Vercel AI SDK, LangChain and more. The free plan needs no card, and the code PHBU7A47FH gets you 1 month of Pro.
What's the hardest part of debugging your agents right now?