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anysite Content Analytics

anysite 内容分析

Measure and optimize content performance across social platforms using anysite MCP. Track engagement, identify top performers, and refine your content strategy.
借助anysite MCP衡量并优化跨社交平台的内容表现。追踪互动数据、识别高表现内容，并优化你的内容策略。

Overview

概述

  • Track post performance across Instagram, YouTube, LinkedIn, Twitter/X
  • Analyze engagement metrics (likes, comments, shares, views)
  • Identify top content and viral patterns
  • Benchmark against competitors for strategy insights
  • Optimize posting strategy based on data
Coverage: 80% - Strong for Instagram, YouTube, LinkedIn, Twitter, Reddit
  • 追踪帖子表现：覆盖Instagram、YouTube、LinkedIn、Twitter/X
  • 分析互动指标（点赞、评论、分享、浏览量）
  • 识别高表现内容及爆款模式
  • 竞品对标获取策略洞察
  • 基于数据优化发布策略
覆盖范围：80% - 在Instagram、YouTube、LinkedIn、Twitter、Reddit平台表现优异

Supported Platforms

支持的平台

  • ✅ Instagram: Posts, Reels, likes, comments, engagement rates
  • ✅ YouTube: Videos, views, likes, comments, watch time indicators
  • ✅ LinkedIn: Posts, articles, reactions, comments, shares
  • ✅ Twitter/X: Tweets, retweets, likes, replies
  • ✅ Reddit: Posts, upvotes, comments, awards
  • ✅ Instagram: 帖子、Reels、点赞、评论、互动率
  • ✅ YouTube: 视频、浏览量、点赞、评论、观看时长指标
  • ✅ LinkedIn: 帖子、文章、互动、评论、分享
  • ✅ Twitter/X: 推文、转发、点赞、回复
  • ✅ Reddit: 帖子、点赞、评论、奖励

Quick Start

快速开始

Step 1: Collect Content Data
Platform-specific:
  • Instagram: 
    get_instagram_user_posts(username, count=50)
  • LinkedIn: 
    get_linkedin_user_posts(urn, count=50)
  • Twitter: 
    get_twitter_user_posts(user, count=100)
  • YouTube: 
    get_youtube_channel_videos(channel, count=30)
Step 2: Analyze Engagement
Calculate metrics:
  • Engagement rate: (likes + comments + shares) / followers
  • Best performing content: Top 10% by engagement
  • Content types: Video vs. image vs. text
  • Posting frequency: Posts per week
Step 3: Identify Patterns
Look for:
  • Best posting times (day of week, time)
  • Top-performing topics/themes
  • Optimal content length
  • High-engagement formats
Step 4: Optimize Strategy
Based on findings:
  • Double down on top content types
  • Post more during peak engagement times
  • Replicate successful topics
  • Adjust content mix
步骤1：收集内容数据
各平台专属方法：
  • Instagram: 
    get_instagram_user_posts(username, count=50)
  • LinkedIn: 
    get_linkedin_user_posts(urn, count=50)
  • Twitter: 
    get_twitter_user_posts(user, count=100)
  • YouTube: 
    get_youtube_channel_videos(channel, count=30)
步骤2：分析互动数据
计算指标：
  • 互动率：(点赞 + 评论 + 分享) / 粉丝数
  • 高表现内容：互动率Top10%的帖子
  • 内容类型：视频 vs 图片 vs 文字
  • 发布频率：每周发帖量
步骤3：识别规律模式
重点关注：
  • 最佳发布时间（星期几、具体时段）
  • 高表现话题/主题
  • 最优内容长度
  • 高互动格式
步骤4：优化策略
基于分析结果：
  • 加大高表现内容类型的产出
  • 在互动高峰时段增加发帖量
  • 复制成功话题的创作思路
  • 调整内容组合比例

Common Workflows

常见工作流

Workflow 1: Instagram Content Audit

工作流1：Instagram内容审计

Steps:
  1. Get All Posts
get_instagram_user_posts(username, count=100)
  1. Calculate Metrics
For each post:
- Engagement rate = (likes + comments) / follower_count
- Engagement per hour = engagement / hours_since_posted
- Content type (Reel, carousel, single image, video)
  1. Identify Top Performers
Sort by engagement rate
Top 10%: Analyze for common patterns
- Topics/themes
- Visual style
- Caption style and length
- Hashtag strategy
  1. Analyze Content Mix
Count by type:
- Reels: X% of posts, Y% of engagement
- Carousels: X% of posts, Y% of engagement
- Single images: X% of posts, Y% of engagement
  1. Benchmark Against Competitors
For each competitor:
  get_instagram_user_posts(competitor, count=50)
Compare:
- Posting frequency
- Engagement rates
- Content types
- Top themes
Expected Output:
  • Content performance report
  • Top 10 performing posts
  • Content type effectiveness
  • Posting frequency analysis
  • Competitive benchmark
步骤：
  1. 获取所有帖子
get_instagram_user_posts(username, count=100)
  1. 计算指标
For each post:
- Engagement rate = (likes + comments) / follower_count
- Engagement per hour = engagement / hours_since_posted
- Content type (Reel, carousel, single image, video)
  1. 识别高表现帖子
Sort by engagement rate
Top 10%: Analyze for common patterns
- Topics/themes
- Visual style
- Caption style and length
- Hashtag strategy
  1. 分析内容组合
Count by type:
- Reels: X% of posts, Y% of engagement
- Carousels: X% of posts, Y% of engagement
- Single images: X% of posts, Y% of engagement
  1. 与竞品对标
For each competitor:
  get_instagram_user_posts(competitor, count=50)
Compare:
- Posting frequency
- Engagement rates
- Content types
- Top themes
预期输出：
  • 内容表现报告
  • 表现Top10的帖子
  • 内容类型有效性分析
  • 发布频率分析
  • 竞品对标结果

Workflow 2: LinkedIn Content Strategy Analysis

工作流2：LinkedIn内容策略分析

Steps:
  1. Collect Post History
get_linkedin_user_posts(urn, count=100)
  1. Categorize Content
Group by type:
- Text-only posts
- Image posts
- Video posts
- Article shares
- LinkedIn articles
- Polls
  1. Analyze Engagement by Type
For each content type:
- Average reactions
- Average comments
- Average shares
- Engagement rate
  1. Topic Analysis
Extract themes from top posts:
- Industry insights
- Personal stories
- How-to/educational
- Company news
- Thought leadership
  1. Posting Timing Analysis
Group posts by:
- Day of week
- Time of day
Calculate average engagement for each group
Expected Output:
  • Best content types for engagement
  • Top topics by engagement
  • Optimal posting times
  • Content frequency recommendations
步骤：
  1. 收集发帖历史
get_linkedin_user_posts(urn, count=100)
  1. 分类内容
Group by type:
- Text-only posts
- Image posts
- Video posts
- Article shares
- LinkedIn articles
- Polls
  1. 按类型分析互动数据
For each content type:
- Average reactions
- Average comments
- Average shares
- Engagement rate
  1. 话题分析
Extract themes from top posts:
- Industry insights
- Personal stories
- How-to/educational
- Company news
- Thought leadership
  1. 发布时段分析
Group posts by:
- Day of week
- Time of day
Calculate average engagement for each group
预期输出：
  • 高互动最优内容类型
  • 高互动热门话题
  • 最佳发布时段
  • 内容发布频率建议

Workflow 3: YouTube Channel Performance Analysis

工作流3：YouTube频道表现分析

Steps:
  1. Get Channel Videos
get_youtube_channel_videos(channel, count=50)
  1. Analyze Each Video
For each video:
  get_youtube_video(video_id)

Metrics:
- Views
- Likes/dislikes
- Comments
- View velocity (views per day since upload)
  1. Identify Patterns
Analyze top 20% by views:
- Video length
- Titles (keywords, style)
- Thumbnail patterns
- Topics/themes
- Upload timing
  1. Engagement Analysis
Check comments:
  get_youtube_video_comments(video_id, count=100)

Analyze:
- Comment quality
- Questions asked
- Sentiment
- Engagement timing
  1. Content Mix Optimization
Compare:
- Long-form (>10 min) vs short (<5 min)
- Tutorial vs entertainment vs review
- Series vs one-offs
Expected Output:
  • Video performance rankings
  • Optimal video length
  • Best topics and formats
  • Title and thumbnail insights
  • Upload strategy recommendations
步骤：
  1. 获取频道视频
get_youtube_channel_videos(channel, count=50)
  1. 分析单个视频
For each video:
  get_youtube_video(video_id)

Metrics:
- Views
- Likes/dislikes
- Comments
- View velocity (views per day since upload)
  1. 识别规律模式
Analyze top 20% by views:
- Video length
- Titles (keywords, style)
- Thumbnail patterns
- Topics/themes
- Upload timing
  1. 互动分析
Check comments:
  get_youtube_video_comments(video_id, count=100)

Analyze:
- Comment quality
- Questions asked
- Sentiment
- Engagement timing
  1. 内容组合优化
Compare:
- Long-form (>10 min) vs short (<5 min)
- Tutorial vs entertainment vs review
- Series vs one-offs
预期输出：
  • 视频表现排名
  • 最优视频长度
  • 最佳话题与格式
  • 标题与封面图洞察
  • 发布策略建议

MCP Tools Reference

MCP工具参考

Instagram

Instagram

  • get_instagram_user_posts(user, count)
    - Get posts with engagement
  • get_instagram_post(post_id)
    - Get detailed post metrics
  • get_instagram_post_likes(post, count)
    - Analyze likers
  • get_instagram_post_comments(post, count)
    - Get comments
  • get_instagram_user_posts(user, count)
    - 获取带互动数据的帖子
  • get_instagram_post(post_id)
    - 获取帖子详细指标
  • get_instagram_post_likes(post, count)
    - 分析点赞用户
  • get_instagram_post_comments(post, count)
    - 获取评论

LinkedIn

LinkedIn

  • get_linkedin_user_posts(urn, count)
    - Get post history
  • get_linkedin_company_posts(urn, count)
    - Company page posts
  • get_linkedin_user_posts(urn, count)
    - 获取发帖历史
  • get_linkedin_company_posts(urn, count)
    - 获取企业主页帖子

Twitter/X

Twitter/X

  • get_twitter_user_posts(user, count)
    - Get tweets
  • search_twitter_posts(query, count)
    - Find trending tweets
  • get_twitter_user_posts(user, count)
    - 获取推文
  • search_twitter_posts(query, count)
    - 查找热门推文

YouTube

YouTube

  • get_youtube_channel_videos(channel, count)
    - All videos
  • get_youtube_video(video)
    - Video details and metrics
  • get_youtube_video_comments(video, count)
    - Comments
  • get_youtube_channel_videos(channel, count)
    - 获取所有视频
  • get_youtube_video(video)
    - 获取视频详情与指标
  • get_youtube_video_comments(video, count)
    - 获取评论

Reddit

Reddit

  • reddit_user_posts(username, count)
    - User's posts
  • search_reddit_posts(query, count)
    - Find popular posts
  • reddit_user_posts(username, count)
    - 获取用户帖子
  • search_reddit_posts(query, count)
    - 查找热门帖子

Key Metrics

核心指标

Engagement Rate:
  • Formula: (Likes + Comments + Shares) / Followers × 100
  • Instagram benchmark: 3-6%
  • LinkedIn benchmark: 2-5% of connections
  • Twitter benchmark: 0.5-1%
Content Performance Score:
Score = (Engagement Rate × 40) +
        (Comments/Likes Ratio × 30) +
        (Share Rate × 30)
Viral Potential Indicators:
  • Engagement rate >2x average
  • High share rate (>5% of engagement)
  • Rapid engagement velocity (50% within 24h)
  • Quality comments (questions, discussions)
互动率：
  • 公式：(点赞 + 评论 + 分享) / 粉丝数 × 100
  • Instagram基准值：3-6%
  • LinkedIn基准值：好友数的2-5%
  • Twitter基准值：0.5-1%
内容表现得分：
Score = (Engagement Rate × 40) +
        (Comments/Likes Ratio × 30) +
        (Share Rate × 30)
爆款潜力指标：
  • 互动率＞平均水平2倍
  • 高分享率（＞互动量的5%）
  • 快速互动增长（24小时内获得50%互动量）
  • 高质量评论（包含问题、讨论）

Output Formats

输出格式

Chat Summary:
  • Top 5 performing posts
  • Key insights and patterns
  • Recommendations for optimization
CSV Export:
  • Post URL, date, type
  • Likes, comments, shares
  • Engagement rate
  • Performance rank
JSON Export:
  • Full post data with metadata
  • Time-series engagement data
  • Historical trends
聊天摘要：
  • 表现Top5的帖子
  • 关键洞察与模式
  • 优化建议
CSV导出：
  • 帖子链接、日期、类型
  • 点赞、评论、分享数
  • 互动率
  • 表现排名
JSON导出：
  • 带元数据的完整帖子数据
  • 时间序列互动数据
  • 历史趋势

Reference Documentation

参考文档

  • METRICS_GUIDE.md - Detailed metrics definitions, calculation formulas, and benchmarks
Ready to analyze content? Ask Claude to help you track performance, identify top content, or optimize your posting strategy!
  • METRICS_GUIDE.md - 详细的指标定义、计算公式及基准值
准备好分析内容了吗？ 让Claude帮你追踪表现、识别高表现内容或优化发布策略！