Fixter. Catch your issues before your users.

    before they churn

    AI native monitoring you run entirely from your coding agent, over MCP.

    or talk to us

    15 minute setup · built for AI coding agents

    The problem

    Right now, your users are your monitoring.

    Fixter is built for the way you build now: with agents.

    How it works

    01

    Your agent sets it up

    Run /fixter:onboard. Logs, traces, and metrics start flowing. About 15 minutes. Any coding agent works.

    claude code — fixter onboarding
    > /fixter:onboard
    detected:next.js + postgres
    wiring opentelemetry...done
    telemetry:logs, traces, metrics flowing
    02

    Issues caught from day one

    Errors grouped by root cause: a million events can be one issue, not a flood. No setup, and you are alerted when a new one appears.

    Issues1,441,032 events · 129 issues
    Error local rowset has no storage resource. tablet_id=17843626…
    C++compute
    1,059,080Ongoing
    AnalysisException failed to get backends by Current Cluster
    JVMfe
    196Ongoing
    ResourceAccessException I/O error on POST
    JVMingestion
    1New
    ClientAbortException java.io.IOException: Broken pipe
    JVMquery
    1New
    grouped by stack fingerprint · the same root cause is one issue, whatever the count
    03

    The root cause, with the fix

    An alert fires overnight. The investigation comes back on its own, two minutes later: root cause, impact, and a pick up command for your coding agent to finish the fix.

    #productionthread
    f
    FixterAPP12:56 AM
    🔴 Latency P95 on GET *mobile-api · criticalAutomatic alert from anomaly detection, no rule configured. Compared against a 28 day baseline.7.1% of requests were too slow in the last 6h. Normally 0.3% do.
    f
    FixterAPP12:58 AM

    Real production incident. The mobile app is returning 503s, error rates hitting 44 to 47% on /current-session and three other routes.

    Root cause: a background sweep kept overrunning its tick interval, holding database pool connections and starving the auth path. One traced request shows a pg.SELECT hung for 555 seconds.

    Action: investigate why the sweep stalled five cycles in a row. That is the entry point. The database was a victim, not the initiator. Queued requests retry on their own once the pool is healthy, so no

    Show more

    🔍 Pick up in Claude Code: zesty-grumpy-salmon-4

    alerts arrive by email or Slack. in Slack, the investigation answers in the thread.

    All of this before your client even notices anything is broken.

    We built the thing we kept wishing existed.

    Kristinalinkedin
    co-founder

    As a product leader at Bolt, I watched 20% of my engineering resource go into just debugging issues instead of building.

    Michaellinkedin
    co-founder

    I ran a payments system moving over €1B a year at EasyPark. The hard part was never the fix, it was the hours of digging just to find what actually broke.

    get started

    Start for free.

    You are 15 minutes from covered.

    or talk to us

    Questions

    Fixter is an AI native monitoring platform for small engineering teams: application performance monitoring, error tracking, and uptime monitoring in one place. It stores your logs, traces, and metrics, alerts you when something matters, and an AI agent investigates the root cause for you. Your AI coding agent sets it up in about 15 minutes.

    Yes, that is the point. You do not need to know the tooling. If you can run two commands in your coding agent, it handles the rest. From then on, Fixter only speaks up when something in production needs you.

    It is the fastest path: the plugin does the whole setup for you. But any MCP client works for querying, Cursor included, and you can wire standard OpenTelemetry by hand with four environment variables. Any language OpenTelemetry supports, Fixter supports.

    Monitoring and alerting never touch your code. They run entirely on the telemetry you send. Investigations work on telemetry alone too, but if you grant read access they get sharper: the agent sees the code behind the failure and hands you a fix that fits your codebase. The repository is cloned into a secure sandbox, used only to solve that problem, and deleted right after. During onboarding it is your own agent editing your repo locally, and you review the diff.

    There is a free plan: 10 GB of logs, traces, and metrics a month, issue tracking, alerts, and querying over MCP, with no credit card and no expiry. Growth (€50) raises the volume and retention; Scale (€150) turns on AI investigations, included in the plan rather than billed per use. The free plan is forever - it is not a trial that expires - and you can upgrade or downgrade any time. See the pricing page for the full breakdown.

    Want the technical detail? It is all in the docs.