HTTP API Integration Pattern

Use Case: Fetch data from REST APIs, transform it, and use it in workflows.

Pattern Structure

Trigger → HTTP Request → [Transform] → [Action] → [Error Handler]

Key Characteristic: External data fetching with error handling

Core Components

1. Trigger

Options:

Schedule - Periodic fetching (most common)
Webhook - Triggered by external event
Manual - On-demand execution

2. HTTP Request Node

Purpose: Call external REST APIs

Configuration:

javascript

{
  method: "GET",                    // GET, POST, PUT, DELETE, PATCH
  url: "https://api.example.com/users",
  authentication: "predefinedCredentialType",
  sendQuery: true,
  queryParameters: {
    "page": "={{$json.page}}",
    "limit": "100"
  },
  sendHeaders: true,
  headerParameters: {
    "Accept": "application/json",
    "X-API-Version": "v1"
  }
}

3. Response Processing

Purpose: Extract and transform API response data

Typical flow:

HTTP Request → Code (parse) → Set (map fields) → Action

4. Action

Common actions:

Store in database
Send to another API
Create notifications
Update spreadsheet

5. Error Handler

Purpose: Handle API failures gracefully

Error Trigger Workflow:

Error Trigger → Log Error → Notify Admin → Retry Logic (optional)

Common Use Cases

1. Data Fetching & Storage

Flow: Schedule → HTTP Request → Transform → Database

Example (Fetch GitHub issues):

1. Schedule (every hour)
2. HTTP Request
   - Method: GET
   - URL: https://api.github.com/repos/owner/repo/issues
   - Auth: Bearer Token
   - Query: state=open
3. Code (filter by labels)
4. Set (map to database schema)
5. Postgres (upsert issues)

Response Handling:

javascript

// Code node - filter issues
const issues = $input.all();
return issues
  .filter(item => item.json.labels.some(l => l.name === 'bug'))
  .map(item => ({
    json: {
      id: item.json.id,
      title: item.json.title,
      created_at: item.json.created_at
    }
  }));

2. API to API Integration

Flow: Trigger → Fetch from API A → Transform → Send to API B

Example (Jira to Slack):

1. Schedule (every 15 minutes)
2. HTTP Request (GET Jira tickets updated today)
3. IF (check if tickets exist)
4. Set (format for Slack)
5. HTTP Request (POST to Slack webhook)

3. Data Enrichment

Flow: Trigger → Fetch base data → Call enrichment API → Combine → Store

Example (Enrich contacts with company data):

1. Postgres (SELECT new contacts)
2. Code (extract company domains)
3. HTTP Request (call Clearbit API for each domain)
4. Set (combine contact + company data)
5. Postgres (UPDATE contacts with enrichment)

4. Monitoring & Alerting

Flow: Schedule → Check API health → IF unhealthy → Alert

Example (API health check):

1. Schedule (every 5 minutes)
2. HTTP Request (GET /health endpoint)
3. IF (status !== 200 OR response time > 2000ms)
4. Slack (alert #ops-team)
5. PagerDuty (create incident)

5. Batch Processing

Flow: Trigger → Fetch large dataset → Split in Batches → Process → Loop

Example (Process all users):

1. Manual Trigger
2. HTTP Request (GET /api/users?limit=1000)
3. Split In Batches (100 items per batch)
4. HTTP Request (POST /api/process for each batch)
5. Wait (2 seconds between batches - rate limiting)
6. Loop (back to step 4 until all processed)

Authentication Methods

1. None (Public APIs)

javascript

{
  authentication: "none"
}

2. Bearer Token (Most Common)

Setup: Create credential

javascript

{
  authentication: "predefinedCredentialType",
  nodeCredentialType: "httpHeaderAuth",
  headerAuth: {
    name: "Authorization",
    value: "Bearer YOUR_TOKEN"
  }
}

Access in workflow:

javascript

{
  authentication: "predefinedCredentialType",
  nodeCredentialType: "httpHeaderAuth"
}

3. API Key (Header or Query)

Header auth:

javascript

{
  sendHeaders: true,
  headerParameters: {
    "X-API-Key": "={{$credentials.apiKey}}"
  }
}

Query auth:

javascript

{
  sendQuery: true,
  queryParameters: {
    "api_key": "={{$credentials.apiKey}}"
  }
}

4. Basic Auth

Setup: Create "Basic Auth" credential

javascript

{
  authentication: "predefinedCredentialType",
  nodeCredentialType: "httpBasicAuth"
}

5. OAuth2

Setup: Create OAuth2 credential with:

Authorization URL
Token URL
Client ID
Client Secret
Scopes

javascript

{
  authentication: "predefinedCredentialType",
  nodeCredentialType: "oAuth2Api"
}

Handling API Responses

Success Response (200-299)

Default: Data flows to next node

Access response:

javascript

// Entire response
{{$json}}

// Specific fields
{{$json.data.id}}
{{$json.results[0].name}}

Pagination

Pattern 1: Offset-based

1. Set (initialize: page=1, has_more=true)
2. HTTP Request (GET /api/items?page={{$json.page}})
3. Code (check if more pages)
4. IF (has_more === true)
   └→ Set (increment page) → Loop to step 2

Code node (check pagination):

javascript

const items = $input.first().json;
const currentPage = $json.page || 1;

return [{
  json: {
    items: items.results,
    page: currentPage + 1,
    has_more: items.next !== null
  }
}];

Pattern 2: Cursor-based

1. HTTP Request (GET /api/items)
2. Code (extract next_cursor)
3. IF (next_cursor exists)
   └→ Set (cursor={{$json.next_cursor}}) → Loop to step 1

Pattern 3: Link Header

javascript

// Code node - parse Link header
const linkHeader = $input.first().json.headers['link'];
const hasNext = linkHeader && linkHeader.includes('rel="next"');

return [{
  json: {
    items: $input.first().json.body,
    has_next: hasNext,
    next_url: hasNext ? parseNextUrl(linkHeader) : null
  }
}];

Error Responses (400-599)

Configure HTTP Request:

javascript

{
  continueOnFail: true,  // Don't stop workflow on error
  ignoreResponseCode: true  // Get response even on error
}

Handle errors:

HTTP Request (continueOnFail: true)
  → IF (check error)
    ├─ [Success Path]
    └─ [Error Path] → Log → Retry or Alert

IF condition:

javascript

{{$json.error}} is empty
// OR
{{$json.statusCode}} < 400

Rate Limiting

Pattern 1: Wait Between Requests

Split In Batches (1 item per batch)
  → HTTP Request
  → Wait (1 second)
  → Loop

Pattern 2: Exponential Backoff

javascript

// Code node
const maxRetries = 3;
let retryCount = $json.retryCount || 0;

if ($json.error && retryCount < maxRetries) {
  const delay = Math.pow(2, retryCount) * 1000; // 1s, 2s, 4s

  return [{
    json: {
      ...$json,
      retryCount: retryCount + 1,
      waitTime: delay
    }
  }];
}

Pattern 3: Respect Rate Limit Headers

javascript

// Code node - check rate limit
const headers = $input.first().json.headers;
const remaining = parseInt(headers['x-ratelimit-remaining'] || '999');
const resetTime = parseInt(headers['x-ratelimit-reset'] || '0');

if (remaining < 10) {
  const now = Math.floor(Date.now() / 1000);
  const waitSeconds = resetTime - now;

  return [{
    json: {
      shouldWait: true,
      waitSeconds: Math.max(waitSeconds, 0)
    }
  }];
}

return [{ json: { shouldWait: false } }];

Request Configuration

GET Request

javascript

{
  method: "GET",
  url: "https://api.example.com/users",
  sendQuery: true,
  queryParameters: {
    "page": "1",
    "limit": "100",
    "filter": "active"
  }
}

POST Request (JSON Body)

javascript

{
  method: "POST",
  url: "https://api.example.com/users",
  sendBody: true,
  bodyParametersJson: JSON.stringify({
    name: "={{$json.name}}",
    email: "={{$json.email}}",
    role: "user"
  })
}

POST Request (Form Data)

javascript

{
  method: "POST",
  url: "https://api.example.com/upload",
  sendBody: true,
  bodyParametersUi: {
    parameter: [
      { name: "file", value: "={{$json.fileData}}" },
      { name: "filename", value: "={{$json.filename}}" }
    ]
  },
  sendHeaders: true,
  headerParameters: {
    "Content-Type": "multipart/form-data"
  }
}

PUT/PATCH Request (Update)

javascript

{
  method: "PATCH",
  url: "https://api.example.com/users/={{$json.userId}}",
  sendBody: true,
  bodyParametersJson: JSON.stringify({
    status: "active",
    last_updated: "={{$now}}"
  })
}

DELETE Request

javascript

{
  method: "DELETE",
  url: "https://api.example.com/users/={{$json.userId}}"
}

Error Handling Patterns

Pattern 1: Retry on Failure

HTTP Request (continueOnFail: true)
  → IF (error occurred)
    └→ Wait (5 seconds)
    └→ HTTP Request (retry)

Pattern 2: Fallback API

HTTP Request (Primary API, continueOnFail: true)
  → IF (failed)
    └→ HTTP Request (Fallback API)

Pattern 3: Error Trigger Workflow

Main Workflow:

HTTP Request → Process Data

Error Workflow:

Error Trigger
  → Set (extract error details)
  → Slack (alert team)
  → Database (log error for analysis)

Pattern 4: Circuit Breaker

javascript

// Code node - circuit breaker logic
const failures = $json.recentFailures || 0;
const threshold = 5;

if (failures >= threshold) {
  throw new Error('Circuit breaker open - too many failures');
}

return [{ json: { canProceed: true } }];

Response Transformation

Extract Nested Data

javascript

// Code node
const response = $input.first().json;

return response.data.items.map(item => ({
  json: {
    id: item.id,
    name: item.attributes.name,
    email: item.attributes.contact.email
  }
}));

Flatten Arrays

javascript

// Code node - flatten nested array
const items = $input.all();
const flattened = items.flatMap(item =>
  item.json.results.map(result => ({
    json: {
      parent_id: item.json.id,
      ...result
    }
  }))
);

return flattened;

Combine Multiple API Responses

HTTP Request 1 (users)
  → Set (store users)
  → HTTP Request 2 (orders for each user)
  → Merge (combine users + orders)

Testing & Debugging

1. Test with Manual Trigger

Replace Schedule with Manual Trigger for testing

2. Use Postman/Insomnia First

Test API outside n8n
Understand response structure
Verify authentication

3. Log Responses

javascript

// Code node - log for debugging
console.log('API Response:', JSON.stringify($input.first().json, null, 2));
return $input.all();

4. Check Execution Data

View node output in n8n UI
Check headers, body, status code
Verify data structure

5. Use Binary Data Properly

For file downloads:

javascript

{
  method: "GET",
  url: "https://api.example.com/download/file.pdf",
  responseFormat: "file",  // Important for binary data
  outputPropertyName: "data"
}

Performance Optimization

1. Parallel Requests

Use Split In Batches with multiple items:

Set (create array of IDs)
  → Split In Batches (10 items per batch)
  → HTTP Request (processes all 10 in parallel)
  → Loop

2. Caching

IF (check cache exists)
  ├─ [Cache Hit] → Use cached data
  └─ [Cache Miss] → HTTP Request → Store in cache

3. Conditional Fetching

Only fetch if data changed:

HTTP Request (GET with If-Modified-Since header)
  → IF (status === 304)
    └─ Use existing data
  → IF (status === 200)
    └─ Process new data

4. Batch API Calls

If API supports batch operations:

javascript

{
  method: "POST",
  url: "https://api.example.com/batch",
  bodyParametersJson: JSON.stringify({
    requests: $json.items.map(item => ({
      method: "GET",
      url: `/users/${item.id}`
    }))
  })
}

Common Gotchas

1. ❌ Wrong: Hardcoded URLs

javascript

url: "https://api.example.com/prod/users"

✅ Correct: Use environment variables

javascript

url: "={{$env.API_BASE_URL}}/users"

2. ❌ Wrong: Credentials in parameters

javascript

headerParameters: {
  "Authorization": "Bearer sk-abc123xyz"  // ❌ Exposed!
}

✅ Correct: Use credentials system

javascript

authentication: "predefinedCredentialType",
nodeCredentialType: "httpHeaderAuth"

3. ❌ Wrong: No error handling

javascript

HTTP Request → Process (fails if API down)

✅ Correct: Handle errors

javascript

HTTP Request (continueOnFail: true) → IF (error) → Handle

4. ❌ Wrong: Blocking on large responses

Processing 10,000 items synchronously

✅ Correct: Use batching

Split In Batches (100 items) → Process → Loop

Real Template Examples

From n8n template library (892 API integration templates):

GitHub to Notion:

Schedule → HTTP Request (GitHub API) → Transform → HTTP Request (Notion API)

Weather to Slack:

Schedule → HTTP Request (Weather API) → Set (format) → Slack

CRM Sync:

Schedule → HTTP Request (CRM A) → Transform → HTTP Request (CRM B)

Use search_templates({query: "http api"}) to find more!

Checklist for API Integration

Planning

Implementation

Use credentials (never hardcode)
Configure proper HTTP method
Set correct headers (Content-Type, Accept)
Handle pagination if needed
Add query parameters properly

Error Handling

Performance

Use batching for large datasets
Add rate limiting if needed
Consider caching
Test with production load

Security

Use HTTPS only
Store secrets in credentials
Validate API responses
Use environment variables

Summary

Key Points:

Authentication via credentials system (never hardcode)
Error handling is critical (continueOnFail + IF checks)
Pagination for large datasets
Rate limiting to respect API limits
Transform responses to match your needs

Pattern: Trigger → HTTP Request → Transform → Action → Error Handler

Related:

webhook_processing.md - Receiving HTTP requests
database_operations.md - Storing API data