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crazyrabbitLTC

Twitter MCP Server

userInfluenceMetrics

Calculate Twitter user influence scores and engagement metrics to analyze reach and audience interaction for any username.

Instructions

Calculate user influence scores and engagement metrics

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
usernameYesUsername to analyze influence metrics for
analyzeEngagementNoInclude engagement analysis (default: true)
analyzeReachNoInclude reach and influence scoring (default: true)

Implementation Reference

  • Core handler function that executes the userInfluenceMetrics tool. Fetches user profile and recent tweets using SocialData client, computes engagement metrics (avg likes/retweets/replies, engagement rate) and reach metrics (follower base, influence score), formats and returns the response.
    export const handleUserInfluenceMetrics: SocialDataHandler<UserInfluenceMetricsArgs> = async ( _client: any, { username, analyzeEngagement = true, analyzeReach = true }: UserInfluenceMetricsArgs ) => { try { const socialClient = getSocialDataClient(); if (!socialClient) { return createMissingApiKeyResponse('User Influence Metrics'); } // Get user profile and recent tweets const [profile, tweets] = await Promise.all([ socialClient.getUserProfile({ username, includeMetrics: true }), socialClient.getUserTweets({ username, maxResults: 20 }) ]); const user = profile.data; const recentTweets = tweets.data || []; // Calculate influence metrics const metrics: any = { user: { username: user.username, followers: user.public_metrics?.followers_count || 0, following: user.public_metrics?.following_count || 0, verified: user.verified || false } }; if (analyzeEngagement && recentTweets.length > 0) { const totalLikes = recentTweets.reduce((sum: number, tweet: any) => sum + (tweet.public_metrics?.like_count || 0), 0); const totalRetweets = recentTweets.reduce((sum: number, tweet: any) => sum + (tweet.public_metrics?.retweet_count || 0), 0); const totalReplies = recentTweets.reduce((sum: number, tweet: any) => sum + (tweet.public_metrics?.reply_count || 0), 0); metrics.engagement = { avg_likes_per_tweet: Math.round(totalLikes / recentTweets.length), avg_retweets_per_tweet: Math.round(totalRetweets / recentTweets.length), avg_replies_per_tweet: Math.round(totalReplies / recentTweets.length), engagement_rate: user.public_metrics?.followers_count > 0 ? Math.round(((totalLikes + totalRetweets + totalReplies) / recentTweets.length / user.public_metrics.followers_count) * 10000) / 100 : 0 }; } if (analyzeReach) { metrics.reach = { follower_base: user.public_metrics?.followers_count || 0, potential_reach: user.public_metrics?.followers_count || 0, estimated_influence_score: Math.min(100, Math.log10((user.public_metrics?.followers_count || 1) + 1) * 20) }; } return createSocialDataResponse( formatAnalytics(metrics, `Influence Metrics for @${username}`) ); } catch (error) { throw new Error(formatSocialDataError(error as Error, 'user influence metrics')); } };
  • Tool schema definition including description and input validation schema for the userInfluenceMetrics tool, used for MCP tool registration.
    userInfluenceMetrics: { description: 'Calculate user influence scores and engagement metrics', inputSchema: { type: 'object', properties: { username: { type: 'string', description: 'Username to analyze influence metrics for' }, analyzeEngagement: { type: 'boolean', description: 'Include engagement analysis (default: true)' }, analyzeReach: { type: 'boolean', description: 'Include reach and influence scoring (default: true)' } }, required: ['username'] } },
  • TypeScript interface defining the input arguments for the userInfluenceMetrics handler.
    export interface UserInfluenceMetricsArgs { username: string; analyzeEngagement?: boolean; analyzeReach?: boolean; }
  • src/index.ts:451-454 (registration)
    Tool dispatch/registration in the main MCP server request handler switch statement, calling the specific handler function.
    case 'userInfluenceMetrics': { const args = request.params.arguments as any; response = await handleUserInfluenceMetrics(client, args); break;
  • src/index.ts:73-83 (registration)
    Import of the handleUserInfluenceMetrics handler function into the main index file for use in tool dispatching.
    handleUserInfluenceMetrics, handleGetFullThread, handleGetConversationTree, handleGetThreadMetrics, handleFindMutualConnections, handleAnalyzeFollowerDemographics, handleMapInfluenceNetwork, handleGetHashtagTrends, handleAnalyzeSentiment, handleTrackVirality } from './handlers/socialdata/index.js';

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