MCP For Claude Marketplace
Twitter CTA and Engagement Scorer

Twitter CTA and Engagement Scorer MCP Connector for Claude

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Analyze Twitter/X posts for engagement effectiveness, classifying CTAs and detecting algorithmic triggers.

4 tools Official Updated Oct 1, 2026 Official Vinkius Partner
More Details Connect to Claude

The Twitter CTA and Engagement Scorer provides a deterministic scoring engine to analyze X (formerly Twitter) posts for engagement effectiveness. It evaluates call-to-action types, detects algorithmic triggers, measures insight density for quote tweets, and calculates structural positioning weight. Use cta_type_tool to classify interaction intent, engagement_triggers_tool to find high-performance phrases, quote_potential_tool to estimate quote tweet incentive via verb density, and positional_weight_tool to determine CTA effectiveness based on its distance from the end of the post.

twitterxengagementctaanalyticssocial-media

4 tools expose this connector's capabilities to your AI agent.

cta_type_tool

Classify the type of Call to Action (CTA) in a tweet

engagement_triggers_tool

Detect high-performance engagement triggers in a tweet

positional_weight_tool

Calculate the effectiveness of CTA placement

quote_potential_tool

Evaluate the potential for a tweet to be quoted/reposted

See how to talk to your AI agent using Twitter CTA and Engagement Scorer.

Analyze this tweet for engagement: 'RT if you agree! This is the best way to learn about MCP.'

The tweet contains an exact match for a retweet trigger. CTA Type: Retweet Bait. Confidence Score: 0.95.

What is the engagement potential of this text: 'I think we should explore new technologies in AI development.'

The insight score is 0.75 based on identified verb density.

Check the CTA position for: 'Check out this link: https://vinkius.com/blog/mcp' where the CTA starts at index 15.

The calculated weight is 0.42, as the CTA is located significantly far from the end of the tweet.

The `engagement_triggers_tool` performs exact string matching against known high-performance phrases like 'RT if you agree' or 'Reply with'.

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