Never Miss a Doc Update That Affects Your Code

AI detects documentation changes and notifies only the users whose integrations are affected. Targeted alerts, not noisy changelogs.


Why this matters

Developers miss important documentation updates for APIs they depend on, leading to integration issues when behavior changes without their knowledge. Changelog emails notify everyone about everything, creating noise that gets ignored. The result is production incidents caused by undiscovered breaking changes in documentation.


How MultiMail solves this

MultiMail's autonomous mode delivers targeted documentation update notifications matched to each user's actual API usage patterns. Instead of a changelog blast, only users who call the affected endpoints receive the notification — relevant alerts that actually get read.

1

Detect Documentation Changes

When documentation, API references, or knowledge base articles are updated, the AI receives the change details including which endpoints, parameters, or behaviors changed.

2

Match to Affected Users

The AI cross-references the changed documentation against each user's actual API usage patterns. Only users who use the affected features receive the notification.

3

Compose Targeted Notification

Each notification explains what changed, why it matters for that user's specific integration, and links to the updated documentation.

4

Send Autonomously

Autonomous mode delivers notifications immediately when docs change. Developers need to know about changes affecting their code as soon as possible.


Implementation

Send Targeted Doc Update Notification
python
import requests

API = "https://api.multimail.dev/v1"
HEADERS = {"Authorization": "Bearer mm_live_xxx"}

def notify_doc_update(change: dict):
    "cm"># Find users who use the affected endpoint
    affected_users = get_users_by_endpoint(change["endpoint"])
    
    for user in affected_users:
        body = (
            f"Hi {user[&"cm">#039;name']},\n\n"
            f"Documentation for {change[&"cm">#039;endpoint']} has been updated.\n\n"
            f"What changed: {change[&"cm">#039;summary']}\n"
            f"Impact to your integration: {change[&"cm">#039;impact']}\n\n"
            f"Updated docs: {change[&"cm">#039;doc_url']}\n\n"
            f"Your integration calls this endpoint approximately "
            f"{user[&"cm">#039;usage_count']} times per day."
        )

        requests.post(
            f"{API}/send",
            headers=HEADERS,
            json={
                "from": "[email protected]",
                "to": user["email"],
                "subject": f"Documentation updated: {change[&"cm">#039;title']}",
                "text_body": body
            }
        )

notify_doc_update({
    "endpoint": "/v1/webhooks",
    "title": "New webhook retry behavior",
    "summary": "Webhooks now retry 5x with exponential backoff instead of 3x linear",
    "impact": "Your webhook handler should expect retries up to 32 minutes after initial failure",
    "doc_url": "https://docs.example.com/webhooks"cm">#retries"
})

Notify users affected by a documentation change based on their API usage.

Batch Notify on Major Doc Releases
python
import requests

API = "https://api.multimail.dev/v1"
HEADERS = {"Authorization": "Bearer mm_live_xxx"}

def send_doc_release_summary(changes: list, users: list):
    for user in users:
        "cm"># Filter to changes relevant to this user
        relevant = [c for c in changes if user_uses_feature(user, c["feature"])]
        
        if not relevant:
            continue
        
        items = "\n".join(
            [f"- {c[&"cm">#039;title']}: {c['summary']}" for c in relevant]
        )
        
        body = (
            f"Hi {user[&"cm">#039;name']},\n\n"
            f"We&"cm">#039;ve updated {len(relevant)} documentation pages "
            f"relevant to your integration:\n\n{items}\n\n"
            f"Full changelog: https://docs.example.com/changelog"
        )

        requests.post(
            f"{API}/send",
            headers=HEADERS,
            json={
                "from": "[email protected]",
                "to": user["email"],
                "subject": f"{len(relevant)} doc updates relevant to your integration",
                "text_body": body
            }
        )

Send a curated summary when multiple documentation pages are updated simultaneously.

MCP Tool Integration
typescript
"cm">// Doc update notification via MCP

"cm">// 1. Find affected users
const users = await mcp.search_contacts({
  tags: ["developer", "uses-webhooks"]
});

"cm">// 2. Send targeted notification
for (const user of users.contacts) {
  await mcp.send_email({
    from: "[email protected]",
    to: user.email,
    subject: "Documentation updated: New webhook retry behavior",
    text_body: `Hi ${user.name}, the webhook docs have been updated. Since your integration uses webhooks, here's what changed...`
  });
}

console.log(`Notified ${users.contacts.length} affected developers`);

Use MultiMail MCP tools for documentation update notifications.


What you get

Signal Over Noise

Users only receive notifications about documentation changes that affect their actual integration, not every change in the entire knowledge base.

Prevent Integration Breakage

Proactive notification of behavior changes gives developers time to update their code before the change causes production issues.

Higher Open Rates

Targeted, relevant notifications get 3-5x higher open rates than generic changelog emails because developers know the content applies to them.

Instant Delivery

Autonomous mode sends notifications as soon as docs are updated. Developers learn about changes before they're surprised by new behavior in production.


Recommended oversight mode

Recommended
autonomous
Documentation update notifications are factual, internal-facing, and time-sensitive. The content is objective (what changed and where to read about it) with no subjective AI prose. Autonomous delivery ensures developers learn about changes immediately.

Common questions

How does the AI know which users are affected?
You provide the mapping between documentation sections and API features. The AI cross-references documentation changes with each user's API usage data (which endpoints they call, which features they use) to determine relevance.
What about breaking changes vs minor updates?
Classify documentation changes by severity in your notification trigger. Breaking changes get immediate, prominent notifications. Minor updates can be batched into weekly digest emails. The AI adjusts urgency and formatting accordingly.
Can users choose which updates they receive?
Yes. Use contact tags to track user notification preferences. Some developers want all updates, others only want breaking changes. The AI filters notifications based on each user's preference tags.
How is this different from a changelog?
A changelog is one document listing everything that changed. These notifications are personalized emails telling each developer specifically what changed that affects their code. It's the difference between a newspaper and a personalized news feed.

Explore more use cases

The only agent email with a verifiable sender

Email infrastructure built for AI agents. Verifiable identity, graduated oversight, and a 38-tool MCP server. Formally verified in Lean 4.