Should I just build my own changelog monitor?

Pick five popular APIs you depend on. Open their changelogs. Now write a parser for each. Easy.

Six weeks later one of them ships a redesign. Below are the things that actually happened to APIDelta's crawler in the last 90 days, in case you think this is hypothetical:

• Stripe shipped a React SPA changelog. The initial HTML response is empty until JS renders. Yourfetch()parser sees zero entries and goes silent. Fix: add headless Chromium, run it on every crawl, ship a Docker image with ~600 MB of browser binaries, and pay for the cold-start cost forever.
• OpenAI blocks plain bot user-agents at the edge. Returns HTTP 403. Fix: a realistic Chrome user-agent string and a render delay. The same delay that breaks every future timeout you set.
• GitHub Blog changed its changelog DOM. The selector that grabbed the title now grabs the date+category meta. Every entry came through as "Apr 28 · Library" with no body, all flagged as noise and dropped. Fix: detect the meta-class and fall back to a different child node. Find this when a user complains nothing's coming through.
• SendGrid retireddocs.sendgrid.com/release-notesafter the Twilio acquisition. The URL just 404s now. Fix: switch to thesendgrid-nodejsGitHub releases page and rewrite the parser for that format.
• AWS'sgeneral/latest/gr/rssfeed went stale around the same time. The canonical URL moved. You find it by reading the page source of an AWS announcement and spelunking through old Reddit threads.

Five vendors. Five different fixes. One weekend, gone. And that's five out of the dozens of changelogs your team actually depends on.

The "is this a breaking change?" classifier is the easy part to write and the hardest part to maintain.

• Model versions get deprecated. Today's prompt that returned clean JSON onclaude-3-5-sonnetstarts hallucinating fields onclaude-4-opus. Your pipeline doesn't crash — it silently mislabels CRITICAL as MEDIUM and your team stops trusting the alerts.
• Vendor changelog conventions shift. Vercel started writing "migrate by" instead of "deprecated" for some changes; your keyword-based fallback misses them. Stripe will say "sunset" one quarter and "decommission" the next.
• Cost tuning. The naive approach sends every changelog entry to the biggest model. At 50 sources × dozens of entries per crawl × 24 crawls a day, that's a real bill. You'll spend a week building a cheap-model-first cascade with a confidence-threshold escalation. Then you'll spend another week tuning the threshold.
• Hallucinations on edge cases. Some changelogs say "this is not a breaking change but..." followed by something that absolutely is. The LLM picks up the disclaimer and labels it NON_BREAKING. You find this when production breaks.

The moment you have two people on the same project, the requirements quietly multiply:

• Alert dedup: rule × change pair, exactly once. If two rules both match a critical Stripe change, you don't want two pings — but if one fails you do want a retry. Get the unique constraint wrong and either people get spammed or they miss the one alert that mattered.
• Severity thresholds per rule: your platform team wants CRITICAL+ to PagerDuty; your dev team wants MEDIUM+ to a Slack channel. Now you need filters, channel routing, and a UI that doesn't look hostile.
• Audit trail: when someone acks a CRITICAL change, you need a log. When the alert failed and you retried it three times, you need a log. When a teammate revokes an integration, you need a log. None of this is hard. All of it is tedious.
• Retry + DLQ: Slack's webhook will return 429. SendGrid will time out. GitHub will transiently 5xx. You will write retry-with-backoff. You will write a dead-letter store. You will write a UI to retry from the dead letter. Each of these is half a day of work you didn't budget for.
• Team invites + seat enforcement: if more than one human will use this, you need invite tokens, expiry, email match, plan-limit checks. Add a few days.

APIDelta's catalog has 39 vetted entries today and is growing. For each entry, the work was:

1. Find the actual changelog URL — not the marketing page.
2. Figure out the format (HTML, RSS, Atom, GitHub Releases, JSON feed).
3. Verify the parser works. Catch the SPA cases. Catch the bot blocks. Update the URL when the vendor moves it.
4. Write a one-line description that's accurate, useful, and not just the marketing copy.
5. Tag it for search. Categorize it. Surface a logo.

If you skip this, your "monitor" is just a textbox that asks users to do all of the above themselves. Most won't. The ones who do will get bad data and blame you.

Slack alerts are a webhook POST. Email alerts are an SMTP send. GitHub Issues are a REST POST with a PAT. Sounds trivial. The real work:

• HMAC-signed outbound webhooks so receivers can verify it's really you. A dedicated rotation flow when secrets leak.
• Per-team API keys for programmatic access. Hashed at rest, prefix shown for identification, one-time reveal on creation, audit logs on use.
• GitHub Issues integration with PAT scoping, label config, severity gating, label-not-found error handling.
• MCP server endpoint so Claude (Desktop, Code, anything else) can query your team's monitored changes directly. Hand-rolled JSON-RPC, Bearer auth, five tools, one settings UI.

Each of these is a couple of days. None of them are hard. All of them are work.

Build it yourself if:

• You only need to monitor 1–2 sources, both with stable RSS feeds.
• You don't need a team workflow — you alone read the alerts.
• You have time to keep parsers patched, classifier prompts tuned, and integrations healthy.
• The above sounds fun, not exhausting.

Use APIDelta if:

• You want to set up monitoring, route alerts, and never think about parser maintenance again.
• You'd rather spend that time on your actual product.
• You want a team workflow with audit trails, integrations, and a curated catalog out of the box.
• $49/month is cheaper than half a day of your time.