N8N automated Twitter reply bot workflow
**N8N Automated Twitter Reply Bot Workflow**
============================================
**For latest version, check**: [dziura.online/automation](https://dziura.online/automation)
Latest [documentation can be find here](https://docs.google.com/document/d/13okk16lkUOgpbeahMcdmd7BuWkAp_Lx6kQ8BwScbqZk/edit?usp=sharing)
**You must have Apify community node installed before pasting the JSON to your workflow.**
**Overview**
------------
This n8n workflow creates an intelligent Twitter/X reply bot that automatically scrapes tweets based on keywords or communities, analyzes them using AI, generates contextually appropriate replies, and posts them while avoiding duplicates. The bot operates on a schedule with intelligent timing and retry mechanisms.
**Key Features**
----------------
* **Automated tweet scraping** from Twitter/X using Apify actors
* **AI-powered reply generation** using LLM (Large Language Model)
* **Duplicate prevention** via MongoDB storage
* **Smart scheduling** with timezone awareness and natural posting patterns
* **Retry mechanism** with failure tracking
* **Telegram notifications** for status updates
* **Manual trigger** option via Telegram command
**Required Credentials & Setup**
--------------------------------
### **1\. Telegram Bot**
* Create a bot via [@BotFather](https://t.me/BotFather) on Telegram
* Get your Telegram chat ID to receive status messages
* **Credential needed**: Telegram account (Bot token)
### **2\. MongoDB Database**
* Set up a MongoDB database to store replied tweets and prevent duplicates
* Create a collection (default name: collection\_name)
* **Credential needed**: MongoDB account (Connection string)
* **Tutorial**: [MongoDB Connection Guide](https://youtu.be/gB76VdlpX7Y?si=bw_LHLTkXEk8LFO0)
### **3\. Apify Account**
* Sign up at [Apify.com](https://apify.com/)
* **Primary actors used**:
* **Search Actor**: [api-ninja/x-twitter-advanced-search](https://apify.com/api-ninja/x-twitter-advanced-search) - For keyword-based tweet scraping (ID: 0oVSlMlAX47R2EyoP)
* **Community Actor**: [api-ninja/x-twitter-community-search-post-scraper](https://apify.com/api-ninja/x-twitter-community-search-post-scraper) - For community-based tweet scraping (ID: upbwCMnBATzmzcaNu)
* **Credential needed**: Apify account (API token)
### **4\. OpenRouter (LLM Provider)**
* Sign up at [OpenRouter.ai](https://openrouter.ai/)
* Used for AI-powered tweet analysis and reply generation
* **Model used**: x-ai/grok-3 (configurable)
* **Credential needed**: OpenRouter account (API key)
### **5\. Twitter/X API**
* Set up developer account at [developer.x.com](https://developer.x.com/)
* **Note**: Free tier limited to ~17 posts per day
* **Credential needed**: X account (OAuth2 credentials)
**Workflow Components**
-----------------------
### **Trigger Nodes**
#### **1\. Schedule Trigger**
* **Purpose**: Runs automatically every 20 minutes
* **Smart timing**: Only active between 7 AM - 11:59 PM (configurable timezone)
* **Randomization**: Built-in probability control (~28% execution chance) to mimic natural posting patterns
#### **2\. Manual Trigger**
* **Purpose**: Manual execution for testing
#### **3\. Telegram Trigger**
* **Purpose**: Manual execution via /reply command in Telegram
* **Usage**: Send /reply to your bot to trigger the workflow manually
### **Data Processing Flow**
#### **1\. MongoDB Query (Find documents)**
* **Purpose**: Retrieves previously replied tweet IDs to avoid duplicates
* **Collection**: collection\_name (configure to match your setup)
* **Projection**: Only fetches tweet\_id field for efficiency
#### **2\. Data Aggregation (Aggregate1)**
* **Purpose**: Consolidates tweet IDs into a single array for filtering
#### **3\. Keyword/Community Selection (Keyword/Community List)**
* **Purpose**: Defines search terms and communities
* **Configuration**: Edit the JSON to include your keywords and Twitter community IDs
**Format**:{
"keyword\_community\_list": \[
"SaaS",
"Entrepreneur",
"1488663855127535616" // Community ID (19-digit number)
\],
"failure": 0
}
#### **4\. Random Selection (Randomized community, keyword)**
* **Purpose**: Randomly selects one item from the list to ensure variety
#### **5\. Routing Logic (If4)**
* **Purpose**: Determines whether to use Community search or Keyword search
* **Logic**: Uses regex to detect 19-digit community IDs vs keywords
### **Tweet Scraping (Apify Actors)**
#### **Community Search Actor**
* **Actor**: api-ninja/x-twitter-community-search-post-scraper
* **Purpose**: Scrapes tweets from specific Twitter communities
**Configuration**:{
"communityIds": \["COMMUNITY\_ID"\],
"numberOfTweets": 40
}
#### **Search Actor**
* **Actor**: api-ninja/x-twitter-advanced-search
* **Purpose**: Scrapes tweets based on keywords
**Configuration**:{
"contentLanguage": "en",
"engagementMinLikes": 10,
"engagementMinReplies": 5,
"numberOfTweets": 20,
"query": "KEYWORD",
"timeWithinTime": "2d",
"tweetTypes": \["original"\],
"usersBlueVerifiedOnly": true
}
### **Filtering System (Community filter)**
The workflow applies multiple filters to ensure high-quality replies:
* **Text length**: >60 characters (substantial content)
* **Follower count**: >100 followers (audience reach)
* **Engagement**: >10 likes, >3 replies (proven engagement)
* **Language**: English only
* **Views**: >100 views (visibility)
* **Duplicate check**: Not previously replied to
* **Recency**: Within 2 days (configurable in actor settings)
### **AI-Powered Reply Generation**
#### **LLM Chain (Basic LLM Chain)**
* **Purpose**: Analyzes filtered tweets and generates contextually appropriate replies
* **Model**: Grok-3 via OpenRouter (configurable)
* **Features**:
* Engagement potential scoring
* User authority analysis
* Timing optimization
* Multiple reply styles (witty, informative, supportive, etc.)
* <100 character limit for optimal engagement
#### **Output Parser (Structured Output Parser)**
* **Purpose**: Ensures consistent JSON output format
**Schema**:{
"selected\_tweet\_id": "tweet\_id\_here",
"screen\_name": "author\_screen\_name",
"reply": "generated\_reply\_here"
}
### **Posting & Notification System**
#### **Twitter Posting (Create Tweet)**
* **Purpose**: Posts the generated reply as a Twitter response
* **Error handling**: Catches API limitations and rate limits
#### **Status Notifications**
* **Success**: Notifies via Telegram with tweet link and reply text
* **Failure**: Notifies about API limitations or errors
* **Format**: HTML-formatted messages with clickable links
#### **Database Storage (Insert documents)**
* **Purpose**: Saves successful replies to prevent future duplicates
* **Fields stored**: tweet\_id, screen\_name, reply, tweet\_url, timestamp
### **Retry Mechanism**
The workflow includes intelligent retry logic:
#### **Failure Counter (If5, Increment Failure Counter1)**
* **Logic**: If no suitable tweets found, increment failure counter
* **Retry limit**: Maximum 3 retries with different random keywords
* **Wait time**: 3-second delay between retries
#### **Final Failure Notification**
* **Trigger**: After 4 failed attempts
* **Action**: Sends Telegram notification about unsuccessful search
* **Recovery**: Manual retry available via /reply command
**Configuration Guide**
-----------------------
### **Essential Settings to Modify**
1. **MongoDB Collection Name**: Update collection\_name in MongoDB nodes
2. **Telegram Chat ID**: Replace 11111111111 with your actual chat ID
3. **Keywords/Communities**: Edit the list in Keyword/Community List node
4. **Timezone**: Update timezone in Code node (currently set to Europe/Kyiv)
5. **Actor Selection**: Enable only one actor (Community OR Search) based on your needs
### **Filter Customization**
Adjust filters in Community filter node based on your requirements:
* Minimum engagement thresholds
* Text length requirements
* Time windows
* Language preferences
### **LLM Customization**
Modify the AI prompt in Basic LLM Chain to:
* Change reply style and tone
* Adjust engagement criteria
* Modify scoring algorithms
* Set different character limits
**Usage Tips**
--------------
1. **Start small**: Begin with a few high-quality keywords/communities
2. **Monitor performance**: Use Telegram notifications to track success rates
3. **Adjust filters**: Fine-tune based on the quality of generated replies
4. **Respect limits**: Twitter's free tier allows ~17 posts/day
5. **Test manually**: Use /reply command for testing before scheduling
**Troubleshooting**
-------------------
### **Common Issues**
1. **No tweets found**: Adjust filter criteria or check keywords
2. **API rate limits**: Reduce posting frequency or upgrade Twitter API plan
3. **MongoDB connection**: Verify connection string and collection name
4. **Apify quota**: Monitor Apify usage limits
5. **LLM failures**: Check OpenRouter credits and model availability
### **Best Practices**
* Monitor your bot's replies for quality and appropriateness
* Regularly update keywords to stay relevant
* Keep an eye on engagement metrics
* Adjust timing based on your audience's activity patterns
* Maintain a balanced posting frequency to avoid appearing spammy
**Documentation Links**
-----------------------
* **Full Documentation**: [Google Doc Guide](https://docs.google.com/document/d/13okk16lkUOgpbeahMcdmd7BuWkAp_Lx6kQ8BwScbqZk/edit?usp=sharing)
* **Latest Version**: [dziura.online/automation](https://dziura.online/automation)
* **MongoDB Setup Tutorial**: [YouTube Guide](https://youtu.be/gB76VdlpX7Y?si=bw_LHLTkXEk8LFO0)
This workflow provides a comprehensive solution for automated, intelligent Twitter engagement while maintaining quality and avoiding spam-like behavior.
