Kyle Seyler
January 22, 2026

Read Time: 8 Minutes
Building apps with Cursor, Claude Code, or Codex changes how quickly you can ship features. UI components, API integrations, database schemas—AI coding tools handle these faster than ever. But when you prompt "add multi-channel notifications to my app," something interesting happens.
The AI generates basic send functions quickly. Then it starts scaffolding routing logic, fallback handling, delivery tracking, template management. The generated code keeps growing. You're suddenly reviewing hundreds of lines of infrastructure you didn't plan to maintain.
This guide covers a better approach: connecting Cursor to Courier's MCP server so it generates working notification code against your actual account, not generic examples.
Without context about your specific setup, AI coding tools default to building notification infrastructure from scratch. They don't know what templates you've already created, what providers you've configured, or how your user data is structured.
The result is generic code that needs adaptation. You end up debugging generated abstractions instead of shipping features.
MCP (Model Context Protocol) solves this by giving AI tools direct access to your Courier account. Cursor can see your templates, check delivery logs, and generate code that matches your actual configuration.
Add the MCP server to your Cursor config:
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// .cursor/mcp.json{"mcpServers": {"courier": {"url": "https://mcp.courier.com","headers": {"api_key": "YOUR_COURIER_API_KEY"}}}}
For Claude Code:
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claude mcp add --transport http courier https://mcp.courier.com --header api_key:YOUR_COURIER_API_KEY
Get your API key at app.courier.com/settings/api-keys.
What changes once MCP is connected: Cursor can now query your actual Courier account. It sees your templates, users, and delivery history. When you ask it to "send a password reset notification," it checks which templates exist and generates code using the right template ID—not a placeholder.

Before asking Cursor to generate implementation code, verify that your Courier configuration works. The CLI lets you test notifications without writing code.
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npm install -g @trycourier/clicourier login
Send a test notification:
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courier send \--user user_123 \--title "Test notification" \--body "Testing from CLI"
Check delivery logs:
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courier logs --user user_123
List your templates:
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courier templates list
If notifications deliver successfully from the CLI, your provider configuration is correct. Now Cursor can generate code with confidence that the underlying setup works.
With MCP connected and your setup validated, Cursor has everything it needs. Here's how to prompt effectively:

Check what you have: > "Show me my notification templates in Courier. Which one handles order confirmations?"
Build against existing templates: > "Create a function that sends the ORDER_SHIPPED template to a user. Include the tracking URL in the data payload."
Debug delivery issues: > "The notification to user_456 didn't arrive. Check Courier logs and tell me what failed."
Add new templates: > "Create a Courier template called COMMENT_NOTIFICATION for when someone comments on a post. Send to push first, fall back to email."
The key difference from prompting without MCP: Cursor validates against your actual account. If you reference a template that doesn't exist, it tells you. If you ask for a channel you haven't configured, it flags it.
Once MCP is connected, here's what becomes straightforward to implement:
A notification center with unread badges, real-time updates, and mark-as-read functionality. Courier provides drop-in React components that handle the WebSocket connections and state management.
iOS and Android push with automatic token management, badge counts, and deep linking on tap. The mobile SDKs handle provider registration (APNs, FCM) and sync tokens to Courier automatically.
iOS SDK documentation → Android SDK documentation → Flutter SDK documentation → React Native SDK documentation →
Send notifications to users' Slack DMs or Teams channels. Courier handles the OAuth flow, user mapping, and Block Kit formatting for rich messages.

Slack integration guide → Teams integration guide →
Let users control which notifications they receive and on which channels. Courier provides a drop-in preference center component and API for custom implementations.

Reminders, drip sequences, and event-triggered workflows. Set up automations that send a series of notifications based on timing or user actions.
The MCP + CLI + Cursor workflow is most effective when:
It's less suited for:
If you're evaluating options, here's how the main platforms compare for AI coding workflows:

API-first platform that brings together developers, PMs, and marketers. Developers get clean APIs and SDKs. PMs get visual workflow builders. Marketers get template management without touching code.
Focuses on the workflow engine layer. Good for teams that want to define notification logic as code.
Open-source option. Self-host if you want full control over infrastructure.
Comes from mobile push notifications. Strong on push and email for consumer engagement.
| Resource | Link |
|---|---|
| MCP Server Setup | courier.com/docs/tools/mcp |
| CLI Reference | courier.com/docs/tools/cli |
| API Documentation | courier.com/docs/reference |
| SDK Overview | courier.com/docs/sdk-libraries/sdks-overview |
| Free Tier | courier.com/pricing |
Related guides:

The Complete Guide to B2B Customer Engagement
Courier provides the notification infrastructure layer for B2B customer engagement, routing messages across email, SMS, push, in-app, Slack, and Teams based on user preferences and product events. Unlike building notification systems in-house—which takes months of engineering time for features like multi-channel routing, preference management, and delivery tracking—Courier handles this infrastructure so product teams can focus on engagement strategy. B2B customer engagement requires multiple layers: notification infrastructure (Courier), customer data platforms (Segment), product analytics (Mixpanel/Amplitude), and channel-specific tools. Companies with strong engagement programs see 15-25% churn reduction. The key is connecting product events to customer communication at the right moment through the right channel, handling complexity like multiple users per account with different notification needs across work channels.
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Courier's support team resolves complex issues 4X faster using parallel investigation. Here's how it works: when a ticket comes in, an AI agent starts exploring the codebase while the support engineer examines actual customer data. The agent traces code paths and searches past investigations. The human reads event logs and forms hypotheses based on real state. Running both simultaneously catches mismatches fast—the agent sees what could cause a problem, the human sees what actually happened. This post breaks down the workflow, tools, and documentation structure that makes it repeatable.
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