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XPOZ MCP Sample Prompts (Twitter / X)

This collection demonstrates the powerful capabilities of XPOZ MCP for Twitter/X data analysis. Each sample includes the prompt and expected use case.

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Written by Xpoz
Updated over a month ago

πŸ” User Analysis Samples

Sample 1: Influencer Profile Analysis

Prompt:

Analyze @elonmusk's Twitter profile. Show me their follower count, verification status,  and when they joined Twitter. Also get their 10 most recent tweets with engagement metrics.

What it demonstrates:
- User profile retrieval by username
- Recent posts with engagement data
- Combining multiple data points

Sample 2: Multiple User Comparison

Prompt:

Compare the Twitter profiles of @BillGates, @WarrenBuffett, and @JeffBezos.  Show their follower counts, tweet frequency, and find their most engaging tweet  from the past month.

What it demonstrates:
- Batch user analysis
- Cross-user comparisons
- Engagement metric analysis

πŸ“Š Content Analysis Samples

Sample 3: Trending Topic Research

Prompt:

Search for tweets about "artificial intelligence" from the past 7 days.  Show me the top 20 most retweeted posts and create a summary of the main themes discussed.

What it demonstrates:
- Keyword-based search
- Date filtering
- Engagement-based ranking
- Trend analysis

Sample 4: Hashtag Campaign Tracking

Prompt:

Find all tweets with #ClimateAction from this month. Calculate total engagement  (retweets + likes + replies) and identify the top 10 contributors.

What it demonstrates:
- Hashtag tracking
- Engagement aggregation
- Influencer identification
- Campaign metrics

Sample 5: Brand Mention Monitoring

Prompt:

Search for tweets mentioning "Tesla" in the past week. Analyze the sentiment,  count how many are positive vs negative, and show me examples of each.

What it demonstrates:
- Brand monitoring
- Sentiment analysis
- Content categorization
- Real-time tracking

🎯 Advanced Analysis Samples

Sample 6: Viral Content Analysis

Prompt:

Find @OpenAI's tweet with ID 1234567890. Get all its retweets, quotes, and replies.  Create a breakdown of how the tweet spread and who the most influential sharers were.

What it demonstrates:
- Individual tweet deep-dive
- Viral spread tracking
- Network analysis
- Influence mapping

Sample 7: Competitive Intelligence

Prompt:

Get the last 50 tweets from @Apple and @Samsung. Compare their posting frequency,  engagement rates, content types (product announcements vs support vs general),  and audience response patterns.

What it demonstrates:
- Competitive analysis
- Content strategy insights
- Engagement benchmarking
- Pattern recognition

Sample 8: Time-Series Analysis

Prompt:

Get all tweets from @NASAwebb between January 1, 2024 and March 31, 2024.  Create a timeline showing tweet volume and engagement trends over time.

What it demonstrates:
- Historical data retrieval
- Time-based filtering
- Trend visualization
- Performance tracking

🌍 Geographic & Demographic Analysis

Sample 9: Multi-Language Content Search

Prompt:

Search for tweets about "δΈ–η•Œζ―" (World Cup) in Chinese from the past month.  Show engagement patterns and top contributors.

What it demonstrates:
- Multi-language support
- International content analysis
- Cultural insights
- Global reach tracking

Sample 10: Location-Based Research

Prompt:

Find tweets about "tech startup" from users in San Francisco from the past 2 weeks.  Identify common themes and top engagement posts.

What it demonstrates:
- Geographic filtering
- Local trend analysis
- Regional insights
- Community mapping

πŸ’Ό Business Intelligence Samples

Sample 11: Product Launch Monitoring

Prompt:

Track tweets about "iPhone 15" from launch day (September 12, 2023) through the next week.  Show hourly tweet volume, sentiment distribution, and top concerns or praise points.

What it demonstrates:
- Event monitoring
- Real-time tracking
- Sentiment analysis
- Customer feedback analysis

Sample 12: Crisis Management

Prompt:

Search for tweets mentioning @AirlineXYZ with keywords "delay" OR "cancelled"  from the past 24 hours. Identify complaint patterns and response rates.

What it demonstrates:
- Crisis detection
- Customer service monitoring
- Response tracking
- Issue categorization

Sample 13: Influencer Discovery

Prompt:

Search for tweets about "sustainable fashion" from the past month with at least  1000 retweets. Identify the authors and analyze their profiles to find potential  brand ambassadors.

What it demonstrates:
- Influencer identification
- Niche expertise finding
- Partnership opportunities
- Audience alignment

πŸ“ˆ Data Export & Reporting

Sample 14: Comprehensive Report Generation

Prompt:

Create a complete report on @YourBrand's Twitter performance for Q3 2024.  Include all tweets, engagement metrics, growth trends, top performing content,  and audience insights. Export as CSV.

What it demonstrates:
- Bulk data extraction
- Performance reporting
- Metric aggregation
- Data export capabilities

Sample 15: Quote Tweet Analysis

Prompt:

Get the post with ID 1234567890 and all its quote tweets. Analyze how different  communities interpreted or commented on the original message.

What it demonstrates:
- Quote tweet tracking
- Context analysis
- Conversation mapping
- Community insights

πŸ”¬ Research & Academic Use Cases

Sample 16: Discourse Analysis

Prompt:

Search for tweets about "climate change" from verified scientists in 2024.  Analyze the vocabulary used, common citations, and engagement from different audiences.

What it demonstrates:
- Academic research support
- Expert identification
- Discourse patterns
- Citation tracking

Sample 17: Political Communication Study

Prompt:

Compare tweets from political leaders @Leader1 and @Leader2 during the same  time period. Analyze messaging strategies, topics covered, and audience engagement.

What it demonstrates:
- Political analysis
- Communication strategy
- Comparative research
- Rhetorical analysis

🎨 Creative & Media Analysis

Sample 18: Media Coverage Tracking

Prompt:

Find all tweets from major news organizations (@CNN, @BBC, @Reuters) about  "space exploration" this year. Track how the narrative evolved over time.

What it demonstrates:
- Media monitoring
- Narrative analysis
- Multi-source tracking
- Story evolution

Sample 19: Content Creator Analytics

Prompt:

Analyze @ContentCreator's posting patterns: what times do they post, what content  types get the most engagement, and how has their strategy evolved over the past 6 months?

What it demonstrates:
- Creator analytics
- Strategy optimization
- Pattern recognition
- Growth insights

Sample 20: Meme & Trend Tracking

Prompt:

Search for the phrase "OK Boomer" over the past year. Track its usage volume over  time, identify key moments of virality, and show demographic patterns in usage.

What it demonstrates:
- Meme tracking
- Viral moment identification
- Cultural analysis
- Temporal patterns

πŸš€ Getting Started Tips

  1. Be Specific: Include exact usernames (with @) and tweet IDs when available

  2. Use Date Ranges: Specify time periods for better results

  3. Request Specific Fields: Ask for the metrics you need (retweets, replies, impressions)

  4. Combine Queries: XPOZ MCP can handle complex multi-step analyses

  5. Iterate: Start broad, then narrow based on initial results

πŸ’‘ Pro Tips

  • Use forceLatest: true when you need real-time data

  • Request only necessary fields to optimize performance

  • Paginate through large result sets for complete data

  • Combine user and content queries for deeper insights

  • Use the startDate and endDate parameters for precise time windows

Note: Replace example usernames, tweet IDs, and dates with actual values for your analysis.

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