MCP For Claude Marketplace
Twitter Authority Signal Calculator

Twitter Authority Signal Calculator MCP Connector for Claude

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Quantify thought-leadership and authority markers in Twitter/X text.

5 tools Official Updated Oct 1, 2026 Official Vinkius Partner
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This MCP server provides a precision analysis suite for quantifying linguistic indicators of authority on social media. Using exact string parsing, it evaluates four key pillars: customer-centricity (the balance of audience vs. self-focused pronouns), data-point density (concentration of empirical evidence like numbers and currency), linguistic certainty (presence of absolute statements), and brand footprint. Use calculate_customer_centricity to measure reader focus, calculate_data_density for evidence tracking, calculate_authority_markers for detecting definitive language, calculate_promotional_ratio for brand analysis, and calculate_verification_signal to identify interaction with established entities.

twitterxsentiment-analysistext-analyticsthought-leadershipcontent-strategy

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

calculate_promotional_ratio

Evaluates the level of self-promotion or brand-centricity in the text

calculate_verification_signal

Detects the presence of handles/mentions that imply interaction with established entities

calculate_data_density

Throws error if word count is zero. Measures the concentration of empirical evidence within the text

calculate_authority_markers

Returns count and list. Quantifies the presence of absolute, high-certainty language

calculate_customer_centricity

Throws error if no pronouns or empty text. Determines how much the content focuses on the reader versus the writer

See how to talk to your AI agent using Twitter Authority Signal Calculator.

Analyze this tweet for authority: 'You must always prioritize your customers. 100% of our success depends on them.'

The text contains high certainty markers ('must', 'always') and a strong data point ('100%'). The customer-centricity ratio is high due to the use of 'You' and 'your'.

Check the data density of this post: 'Revenue grew by $50,000, representing a 12% increase in Q3.'

The text shows high data density with three distinct points: '$50,000', '12%', and 'Q3'.

How much self-promotion is in this text: 'I am excited to announce our new product launch at @TechCorp!'

The text contains one brand/entity mention (@TechCorp) and uses self-focused pronouns ('I', 'our'), indicating a promotional signal.

The `calculate_customer_centricity` tool compares the frequency of audience-focused pronouns (like 'you' or 'your') against self-focused pronouns (like 'I', 'we', or 'my') to determine if the content prioritizes the reader.

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