HyperProbe is useful when something is going wrong in production but the logs do not contain the value that explains it. It can capture local variables and the stack from a real request without adding a log line, shipping another build, or restarting the service. That turns a deploy-and-wait debugging loop into a targeted check that can be finished in minutes.
This is especially valuable for intermittent failures, silent write errors, race conditions, and changes in third-party responses. Logs and traces can show which request failed, but they often cannot show the exact state the code used at that moment. Seeing several concurrent requests read the same balance, or seeing the upstream field that no longer matches the application model, gets much closer to the cause than adding more general-purpose telemetry.
The MCP integration also fits the job well. A coding agent can follow a hypothesis to a specific line, place a short-lived probe, collect a few real examples, and let the probe expire. Hit limits, expiry times, and the pause-budget guardrail make that practical for focused production investigations rather than leaving a debugger attached indefinitely.
Hyperprobe
AI agents write and ship almost all our code to production. So when something breaks in production at 2AM, nobody can explain why the running system behaved that way.
Worse, these failures don't reproduce locally. They pass tests and code review. So when they fire in prod, your agent guesses from logs and traces that never captured the in-memory state at failure. Engineers add console.logs, redeploy, and wait, while the issue keeps bleeding users.
HyperProbe eliminates this loop. When something breaks at 2AM, your agent (Claude Code, Codex, Cursor) can now drop read-only probes into the running service using our MCP, and capture the exact variable values logs, traces never had. Probes are non-blocking and add zero-overhead. So instead of guessing and burning thousands of tokens, agents debug live issues like a local repro, without risking more downtime.
One of our users solved a payments issue in 9.5 minutes that previously took their engineers 4 hours.
We think the shape of telemetry will change from always-on to on-demand with agents. We have both spent years building and running production at scale, previously at OYO and LimeTray. We have seen how the context engineers carry was critical to running systems reliably. That context is shrinking fast with coding agents.
We'd love feedback from engineers and teams shipping fast who want their agents to have safe eyes and ears into running code. When was the last time you were pulled into a war room for something you could have fixed in 10 minutes if you had the right data?
Find a time at hyperprobe.co or write to shailendra@hyperprobe.co or karan@hyperprobe.co
👉 Add the SDK to your backend, plug our MCP into Cursor/Claude Code in 60 seconds and let it debug a issue in your staging environment (move to prod later)
@shailendra_singh_ht giving cursor actual prod context instead of making it guess from old logs is so smart, congrats for launch
OneCLI
Interesting approach, does customer sensitive data leave the application ever? How does this not affect certifications like soc2, gdpr, HIPAA etc
Hyperprobe
@guyb all data redaction happens in process before leaving your app containers, at no point of time we store, process or receive sensitive data
Callbook.ai - Zoho CRM
Is this platform agnostic?
Is the service only limited by capture history? I have a system with millions of transactions a day. Will the professional plan suit me?
Hyperprobe
@daniel_martinez19 yes, supports all popular languages. We charge by number of backend services you instrument with our SDK. You are not limited by probes or snapshots. It is meant for apps with millions of transactions because isolating errors in those systems becomes that much hard. Book a demo with me from our site or write to shailendra@hyperprobe.co.
my question is does it affect my app data or not and second thing is when i use multiples apps at once dose it work smooth ?
Hyperprobe
@donald_leo sensitive user data can be redacted during capture itself. Also this data can always remain in your VPC if you self-host. You can setup our SDK in as many apps as you need
Lancepilot
Hyperprobe
@priyankamandal yes 50mb additional memory footprint when probes fire. We have benchmarked this for 3000 RPS
OneCLI
How do you make sure this doesn't slow down my app?
Hyperprobe
@jonathan_haim_fishner each sdk is designed to be performant under load. For worst case scenarios, perforance guardrails on cpu, memory, network, latency ensures that all data collection happens only when your app can afford the compute.
How do you handle sensitive product data when the probes capture variable state?
Hyperprobe
@renly_borris we do PII redaction in-process at the exact time the data is captured.