SendGrid (delivery metrics) sits alone in Amplitude.
Judging transactional email health monitor also takes correlate drops with GitHub deployments, and that never shares a screen with Amplitude.
Your incident review is only as fresh as the slowest tab. Email deliverability drops are invisible until customers complain. Yet the inputs sit split across Slack, Amplitude, and GitHub.
Now your agent can fix it.
Judging transactional email health monitor also takes correlate drops with GitHub deployments, and that never shares a screen with Amplitude.
To monitor SendGrid delivery rates you'd merge correlate drops with GitHub deployments with sendgrid (delivery metrics) by hand, every single time.
Slack sees check Sentry for errors shift before anyone, yet the incident review owner hears about it last.
Under The Hood
SendGrid (delivery metrics)
Sentry (errors)
GitHub (deploys)
Transactional Email Health Monitor's brief: Monitor SendGrid delivery rates, correlate drops with GitHub deployments, check Sentry for errors, alert when email health degrades, track impact via Amplitude. Sorted by what needs you first.
The Context Store
Before the prompt runs, the Context Store has matched SendGrid (delivery metrics), Sentry (errors), GitHub (deploys), Slack (alerts), Amplitude (impacted flows) from Slack, Amplitude, and GitHub and 2 more onto one incident record. Transactional email health monitor just reads it, no ID-stitching.
Your agent queries one surface instead of three APIs. Faster responses, lower cost per query, and results that work because the relationships were built before you asked the question.
The Prompt
Two steps. Your data, your results, under 60 seconds.
Build me a transactional email health monitor: read Amplitude, GitHub, and Slack and hand back one brief.
SETUP
Use Airbyte's Agent MCP. 5+ connected sources behind one natural-language surface.
WORKFLOW
list connectors -> link Amplitude, GitHub, and Slack -> pull SendGrid (delivery metrics), Sentry (errors), GitHub (deploys), Slack (alerts), Amplitude (impacted flows) -> join on the incident key -> analyze. An unlinked tool returns a self-describing prompt; a one-off connect step and retry.
TASK
Monitor SendGrid delivery rates, correlate drops with GitHub deployments, check Sentry for errors, alert when email health degrades, track impact via Amplitude, then give me a single brief: sorted by what needs me first, each line with the why and the move.The Outcome
10x
10x speed: transactional email health monitor turns a 2-hour incident review into under a minute.
90%
~90% cheaper: Transactional Email Health Monitor reuses the 5 connectors you already pay for.
3 -> 1
3 -> 1: transactional email health monitor answers Amplitude, GitHub, and Slack in a single query.
Based on internal benchmarks comparing Context Store queries to sequential API calls across equivalent datasets.
01 · Output
Transactional Email Health Monitor ranks each incident by risk, not by name. The top of the list is where to start.
02 · Signal
When GitHub and Amplitude disagree on monitor SendGrid delivery rates, the gap is flagged. Not averaged into a guess.
03 · Context
Each line carries its evidence. Correlate drops with GitHub deployments pulled from GitHub and Slack. Right where you read it.
04 · Action
Transactional Email Health Monitor closes each incident with a recommendation. Who to contact and what to send. Ready to run.
05 · Brief
The brief arrives meeting-ready: SendGrid (delivery metrics) first, sources attached, Amplitude, GitHub, and Slack reconciled.
Aggregates an engineer's contributions across code shouldn't take a morning of tab-switching across Notion, GitHub, and Jira. Performance reviews require quantifying months of contributions across multiple systems; tedious data gathering that engineers dread.
The data for your incident review already exists in Jira / Intercom / GitHub. The problem is no one view joins it. Bug reports in support take days to reach engineering.
Engineering teams run incident reviews on stale, scattered data: GitHub / Jira / Notion each hold a piece, none hold the whole. Code review quality depends on context beyond the diff; what's the broader project goal? What patterns does this codebase follow? What did the related ticket specify? This means joining GitHub data with Jira data with Confluence specs, each with different API patterns and rate limits.
Didn't find your answer? Please don't hesitate to reach out.
What Amplitude data does Transactional Email Health Monitor touch?
What if a incident shows up in two of Amplitude, GitHub, and Slack?
Can I tweak what Transactional Email Health Monitor returns?
Why not call the Amplitude, GitHub, and Slack APIs directly to monitor SendGrid delivery rates?
Connect Amplitude, GitHub, and Slack (plus 50+ more) and ship transactional email health monitor today to monitor SendGrid delivery rates.