rednote-analyzer-mcp 0.1.0

An MCP server that enables LLMs to analyze, understand, and generate RedNote (小红书) content through structured tools and prompts.

RedNote Analyzer MCP

An MCP server that enables AI assistants (Claude, GPT, etc.) to search, analyze, and generate RedNote (小红书/Xiaohongshu) content through structured tools and prompts.

English | 中文

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What is this?

RedNote Analyzer MCP connects your AI assistant to the world of RedNote (小红书) — China's most popular lifestyle and content sharing platform.

Once installed, you can talk to Claude (or any MCP-compatible LLM) in natural language and it will:

• Search for real RedNote content by topic
• Analyze what makes certain posts go viral
• Find patterns across hundreds of notes (title styles, engagement, tags)
• Generate new post outlines optimized for RedNote's audience
• Rewrite your existing text into RedNote-friendly style

Who is this for?

• Content creators who post on RedNote and want data-driven insights
• Marketers researching trends and engagement patterns on the platform
• Investors tracking discussion about US stocks (美股) and financial topics on RedNote
• Developers building tools around RedNote content analysis
• Researchers studying social media content patterns

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Quick Start

Step 1: Install

# Option A: Using pip
pip install rednote-analyzer-mcp

# Option B: Using uv (recommended)
uv tool install rednote-analyzer-mcp

Step 2: Connect to your AI assistant

Claude Desktop — Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "rednote-analyzer-mcp": {
      "command": "uvx",
      "args": ["rednote-analyzer-mcp"]
    }
  }
}

Where is claude_desktop_config.json?

• macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
• Windows: %APPDATA%\Claude\claude_desktop_config.json

Create the file if it doesn't exist.

Claude Code (CLI):

claude mcp add rednote-analyzer-mcp -- uvx rednote-analyzer-mcp

Step 3: Start chatting!

Open Claude and try these prompts:

"Search for trending posts about US stocks (美股) on RedNote"

"Analyze the content patterns of popular investment notes on RedNote"

"Help me write a RedNote post about ETF investing for beginners"

That's it! The server ships with built-in sample data covering investment, tech, lifestyle, and fashion — so everything works out of the box with zero configuration.

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What can it do? (Tools Reference)

This MCP server provides 6 tools and 3 prompts. Here's what each one does, with examples of how to use them in conversation.

Tool 1: rednote_search_notes

Search RedNote notes by keyword or topic.

Finds notes matching your query, sorted by popularity or recency. Supports Chinese and English keywords.

Parameter	Type	Default	Description
query	string	(required)	Search keyword (e.g., "美股", "穿搭", "iPhone")
sort	string	"hot"	Sort order: "hot" (most popular), "recent" (newest), "relevant"
limit	int	20	Max results (1-100)

Example prompts that use this tool:

"Search for RedNote posts about AI stocks"

"Find the most recent posts about spring fashion on RedNote"

"搜索小红书上关于基金定投的热门笔记"

What you get back: A list of notes with title, author, likes, bookmarks, comments, tags, and publish time.

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Tool 2: rednote_get_note_detail

Get the full content of a specific note.

Retrieves complete note content including text body, images, all engagement metrics, author info, and optionally the comments section.

Parameter	Type	Default	Description
note_id	string	(required)	The note's unique ID (from search results)
include_comments	bool	false	Also fetch the comments

Example prompts:

"Show me the full content of note_002"

"Get the details of that NVDA post, including comments"

What you get back: Full note text, image URLs, engagement metrics (likes/collects/comments/shares), author details, tags, topics, location, and publish time. Optionally includes reader comments with likes and reply threads.

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Tool 3: rednote_analyze_note

Deep analysis of a note's structure, sentiment, and patterns.

Breaks down a note into its components: what title technique was used, what content type it is, whether the sentiment is positive/negative, what hooks and CTAs are used, emoji density, and more.

Parameter	Type	Default	Description
note_id	string	""	Note ID to analyze (fetches from data source)
content	string	""	OR provide raw text to analyze directly
title	string	""	Title text (used with content param)

You can either provide a note_id (it will fetch the note) or paste content + title directly.

Example prompts:

"Analyze note_001 — what makes it engaging?"

"Analyze this text as a RedNote post: '今天分享一下我的投资心得...'"

What you get back:

Field	Description	Example values
title_pattern	Title writing technique	question, number_list, emotional_hook, how_to, story, contrast, authority_claim
content_type	Content category	干货 (tutorial), 情绪 (emotional), 观点 (opinion), 经历 (experience), 测评 (review)
sentiment	Overall sentiment	positive, negative, neutral, mixed
engagement_level	Based on like count	viral (10K+), popular (1K-10K), moderate (100-1K), low (<100)
hooks	Identified hooks	Opening line, CTA keywords
call_to_action	CTA phrase if found	"评论区聊聊", "你们觉得", "关注我"
emoji_density	Emojis per 100 chars	2.5
paragraph_count	Number of paragraphs	5
has_list	Uses numbered/bullet lists	true / false
word_count	Character count	350
summary	Human-readable summary	"A viral tutorial note with number_list title pattern. Sentiment: positive. 5 paragraphs, 8 emojis."

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Tool 4: rednote_extract_patterns

Batch analysis: find patterns across many notes on a topic.

This is the power tool. It searches for multiple notes on a topic, analyzes them all, and tells you what the common patterns are — what title styles work, what content types dominate, which tags are popular, and what the average engagement looks like.

Parameter	Type	Default	Description
query	string	(required)	Topic to analyze (e.g., "美股投资", "iPhone测评")
limit	int	20	Number of notes to analyze

Example prompts:

"What are the common patterns in popular US stock posts on RedNote?"

"Analyze the top 20 iPhone review posts — what patterns do viral ones share?"

"提取小红书上关于基金定投的爆款规律"

What you get back:

Field	Description
notes_analyzed	How many notes were analyzed
title_patterns	Distribution: e.g., {"number_list": 8, "emotional_hook": 5, "question": 4, ...}
content_types	Distribution: e.g., {"干货": 10, "测评": 5, "经历": 3, ...}
common_tags	Top 10 most used hashtags
avg_likes	Average likes across analyzed notes
avg_collects	Average bookmarks
insights	Key findings (e.g., "Most common title pattern: number_list", "High average engagement — this is a hot topic")
top_performing_titles	Top 5 best-performing titles (by likes)

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Tool 5: rednote_generate_post

Generate a structured RedNote post outline.

Creates a post template with title suggestions, content structure, hashtags, and posting tips. Supports 5 content styles and 5 content verticals.

Parameter	Type	Default	Description
topic	string	(required)	What to write about
style	string	"干货"	Content style (see below)
vertical	string	"general"	Content vertical (see below)
target_audience	string	""	Optional audience description

Styles:

Style	Meaning	Structure	Tone
干货	Tutorial / how-to	Hook → Key Points (numbered) → Summary → CTA	Informative, helpful, structured
情绪	Emotional content	Emotional hook → Story → Insight → CTA	Personal, emotional, relatable
测评	Product review	Overview → Pros → Cons → Verdict	Objective, detailed, comparison-focused
经验	Personal experience	Background → What happened → Lessons → Advice	Personal, authentic, storytelling
casual	Casual sharing	Hook → Body → CTA	Friendly, conversational, approachable

Verticals:

Vertical	Auto-tags	Notes
investment	#投资 #理财 #美股	Auto-adds risk disclaimer
tech	#数码 #科技 #测评
lifestyle	#生活方式 #日常
fashion	#穿搭 #时尚 #OOTD
general	(none)

Example prompts:

"Generate a RedNote post about ETF investing for beginners, tutorial style"

"Create a review-style post outline for iPhone 17 Pro"

"帮我写一篇关于极简生活的小红书文案，经验分享风格"

What you get back: Title suggestions, content outline with structure guidance, suggested hashtags, posting tips (best times, emoji usage, cover image advice), and an investment disclaimer if the topic involves financial content.

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Tool 6: rednote_rewrite_in_style

Transform any text into RedNote-optimized style.

Takes your raw text and provides a detailed rewrite plan: what to change, how to structure it, what tone to use, where to add emojis and hooks.

Parameter	Type	Default	Description
content	string	(required)	Your original text to rewrite
style	string	"casual"	Target style (same 5 options as generate)
reference_note_id	string	""	Optional: mimic the style of this specific note

Example prompts:

"Rewrite this paragraph in RedNote casual style: 'Today I want to talk about my investment strategy...'"

"Take this product review and make it RedNote-friendly in 测评 style"

"把这段文字改写成小红书风格: '基金定投是一种长期投资策略...'"

What you get back:

Field	Description
rewritten	The original text wrapped with detailed style guidelines for the LLM to follow
title_suggestion	A suggested title for the rewritten content
hashtags	Suggested hashtags
changes	List of specific changes to make (e.g., "Add emojis", "Break into short paragraphs", "Add a hook in the first line")
style_notes	Description of the target style and tone

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Prompts (Workflow Templates)

Prompts are pre-built multi-step workflows. When you use a prompt, the AI assistant automatically chains multiple tools together.

Prompt 1: analyze_trending

Full trend analysis workflow.

Input: a topic (e.g., "美股")

What Claude does automatically:

1. Searches for notes on the topic
2. Extracts patterns across all results
3. Picks 2-3 interesting notes for deep analysis
4. Summarizes findings: best title patterns, content styles, common hashtags, creator insights

How to trigger: Ask Claude to "analyze trending content about [topic] on RedNote" or use the prompt directly in Claude Desktop's prompt selector.

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Prompt 2: write_post

Research-driven post writing workflow.

Input: a topic + style (e.g., "基金定投", "干货")

What Claude does automatically:

1. Researches what works for this topic (pattern extraction)
2. Generates a post template
3. Writes a complete post in Chinese with: catchy title, engaging hook, structured body with emojis, interactive CTA, relevant hashtags

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Prompt 3: investment_briefing

Specialized investment content workflow.

Input: a stock ticker or investment topic (e.g., "NVDA", "美股入门")

What Claude does automatically:

1. Searches for existing investment posts on this topic
2. Analyzes engagement patterns
3. Generates an investment post that: explains concepts simply, includes data/analysis, has proper risk disclaimers (⚠️ 投资有风险), ends with engagement CTA

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Sample Data

The server ships with 10 built-in sample notes covering diverse topics. No configuration needed — these work out of the box:

Note ID	Title	Topic	Likes
note_001	我靠美股赚了第一个10万	US Stock Investing	15,234
note_002	2026年最值得关注的5只AI股票	AI Stocks	28,901
note_003	小白也能懂的基金定投指南	Fund Investing	5,621
note_004	iPhone 17 Pro 深度测评	Tech Review	42,150
note_005	NVDA暴跌15%！发生了什么？	Stock Analysis	31,200
note_006	30天极简生活挑战	Lifestyle	18,500
note_007	为什么我从A股转战美股？	Investing	8,900
note_008	MacBook Pro M5 vs M4 实测对比	Tech Review	35,000
note_009	月薪8000如何理财？	Personal Finance	12,300
note_010	2026春季穿搭灵感	Fashion	24,000

Search keywords that work with mock data: 美股, 投资, AI, iPhone, MacBook, 理财, 穿搭, 极简, NVDA, 基金, 定投

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Using Real Data (Playwright Adapter)

Want to search real RedNote content instead of sample data? The Playwright adapter launches a headless browser to fetch live content from xiaohongshu.com.

Setup

# 1. Install with browser support
pip install rednote-analyzer-mcp[browser]

# 2. Install Chromium browser engine
playwright install chromium

# 3. First run: log in interactively (opens a browser window)
REDNOTE_ADAPTER=playwright REDNOTE_HEADLESS=false rednote-analyzer-mcp
# → Browser opens xiaohongshu.com → Log in with your phone number → Cookies are saved automatically

# 4. Subsequent runs: headless mode (no browser window)
REDNOTE_ADAPTER=playwright rednote-analyzer-mcp

Claude Desktop Config (Real Data)

{
  "mcpServers": {
    "rednote-analyzer-mcp": {
      "command": "uvx",
      "args": ["rednote-analyzer-mcp[browser]"],
      "env": {
        "REDNOTE_ADAPTER": "playwright",
        "REDNOTE_HEADLESS": "true"
      }
    }
  }
}

Note: Xiaohongshu requires login to view search results. The Playwright adapter saves cookies after your first interactive login so you don't have to log in again.

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Environment Variables

Variable	Default	Description
REDNOTE_ADAPTER	mock	Data source: mock (built-in sample data) or playwright (real browser)
REDNOTE_HEADLESS	true	Browser mode: set to false for first-time interactive login
REDNOTE_COOKIE_PATH	~/.rednote-mcp/cookies.json	Custom path for cookie storage

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Architecture

Your AI Assistant (Claude / GPT / etc.)
         ↕ MCP Protocol (stdio)
   RedNote Analyzer MCP Server
         ↕ Adapter Interface
┌──────────────────────────────────────┐
│  MockAdapter    - Built-in samples   │
│  PlaywrightAdapter - Real browser    │
│  YourAdapter    - Custom impl        │
└──────────────────────────────────────┘

Key design decisions:

• Adapter pattern — Data fetching is decoupled from analysis logic. Switch data sources with one env var.
• Pydantic models — All data flows through validated, typed models with JSON schema auto-generation.
• FastMCP — Lightweight Python MCP SDK with decorator-based tool registration.
• Lazy browser init — Playwright only starts Chromium on first request, not at server startup.

Custom Adapter

Want to use your own data source (API, database, etc.)? Implement the RedNoteAdapter interface:

from rednote_analyzer_mcp.adapters.base import RedNoteAdapter
from rednote_analyzer_mcp.models import RedNoteNote, RedNoteComment

class MyAdapter(RedNoteAdapter):
    async def search_notes(self, query, sort="hot", limit=20):
        # Return (list[RedNoteNote], total_count)
        ...

    async def get_note_detail(self, note_id):
        # Return RedNoteNote or None
        ...

    async def get_note_comments(self, note_id, limit=20):
        # Return list[RedNoteComment]
        ...

    async def get_author_notes(self, author_id, limit=20):
        # Return list[RedNoteNote]
        ...

---

Development

# Clone and install
git clone https://github.com/ShellyDeng08/rednote-analyzer-mcp.git
cd rednote-analyzer-mcp
uv sync

# Run linter
uv run ruff check src/

# Run tests
uv run pytest

# Test with MCP Inspector (web UI)
uv run mcp dev src/rednote_analyzer_mcp/server.py

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Compliance

• This project does not contain scraping/crawling code — the browser adapter navigates pages like a normal user
• Investment-related content automatically includes risk disclaimers
• Please comply with Xiaohongshu's Terms of Service and applicable laws
• Sample data is fictional and for development/testing only

License

MIT

---

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中文文档

这是什么？

RedNote Analyzer MCP 是一个 MCP 服务器，让 AI 助手（如 Claude、GPT）能够搜索、分析和生成小红书内容。

安装后，你可以用自然语言跟 Claude 对话：

"搜索小红书上关于美股的热门笔记"

"分析这些笔记的爆款规律"

"帮我写一篇关于基金定投的小红书文案"

"把这段文字改写成小红书风格"

AI 会自动调用工具完成所有操作，并返回结构化的分析结果。

---

快速开始

安装

pip install rednote-analyzer-mcp

添加到 Claude Desktop

在 claude_desktop_config.json 中添加：

{
  "mcpServers": {
    "rednote-analyzer-mcp": {
      "command": "uvx",
      "args": ["rednote-analyzer-mcp"]
    }
  }
}

配置文件位置：

• macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
• Windows: %APPDATA%\Claude\claude_desktop_config.json

添加到 Claude Code

claude mcp add rednote-analyzer-mcp -- uvx rednote-analyzer-mcp

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功能一览

6 个工具

工具	功能	示例用法
rednote_search_notes	按关键词搜索笔记	"搜索关于美股的笔记"
rednote_get_note_detail	获取笔记完整内容和评论	"查看 note_002 的详情"
rednote_analyze_note	分析笔记结构、情感、互动	"分析这篇笔记为什么是爆款"
rednote_extract_patterns	批量分析，提取爆款规律	"分析美股类笔记的共性"
rednote_generate_post	生成帖子大纲和标题	"帮我写一篇关于ETF的文案"
rednote_rewrite_in_style	将文字改写为小红书风格	"把这段话改成小红书风格"

3 个提示词模板

模板	功能	输入
analyze_trending	热门趋势分析（搜索→分析→总结）	主题（如"美股"）
write_post	数据驱动写文案（研究→生成→创作）	主题 + 风格
investment_briefing	投资内容专用创作（含风险提示）	股票代码或投资主题

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分析能力详解

标题类型识别

系统自动识别 7 种常见小红书标题类型：

类型	中文名	识别特征	示例
question	问句式	含"?"、"吗"、"呢"	"为什么我从A股转战美股？"
number_list	数字列表	含数字+量词	"5只AI股票🤖深度分析"
emotional_hook	情绪钩子	含"震惊"、"绝了"、"！"	"NVDA暴跌15%！发生了什么？"
how_to	教程式	含"如何"、"怎么"、"指南"	"小白也能懂的基金定投指南"
story	故事式	含"我"、"经历"、"亲测"	"我靠美股赚了第一个10万"
contrast	对比式	含"vs"、"对比"、"还是"	"MacBook M5 vs M4 实测对比"
authority_claim	权威声明	含"深度"、"专业"、"分析"	"2026年AI行业深度研究报告"

内容分类

类型	识别关键词
干货（教程）	步骤、方法、教程、指南、第一步、✅、📌
情绪	感动、哭了、太难了、崩溃、开心、幸福
观点	我认为、我觉得、我的看法、观点、分析
经历	我的经历、亲身、真实体验、分享一下
测评	测评、评测、优点、缺点、推荐、值不值

情感分析

基于关键词的情感分类：正面、负面、中性、混合。

互动等级

等级	点赞范围
viral 爆款	10,000+
popular 热门	1,000 - 10,000
moderate 一般	100 - 1,000
low 低互动	< 100

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5 种内容风格

生成和改写工具支持 5 种风格：

风格	内容结构	语气	Emoji密度
干货	钩子 → 要点（编号） → 总结 → 互动	专业、实用、有条理	适中
情绪	情感钩子 → 故事 → 感悟 → 互动	个人、感性、有共鸣	多
测评	概览 → 优点 → 缺点 → 结论	客观、详细、对比	适中
经验	背景 → 经过 → 教训 → 建议	个人、真实、叙事	中等
casual	钩子 → 正文 → 互动	友好、随意、亲切	多

---

使用真实数据

默认使用内置的 10 条模拟数据。要获取真实小红书数据：

# 1. 安装浏览器适配器
pip install rednote-analyzer-mcp[browser]
playwright install chromium

# 2. 首次运行：打开浏览器登录（必须）
REDNOTE_ADAPTER=playwright REDNOTE_HEADLESS=false rednote-analyzer-mcp
# → 浏览器打开小红书 → 扫码或手机号登录 → Cookie 自动保存到 ~/.rednote-mcp/cookies.json

# 3. 之后运行：无头模式（后台运行）
REDNOTE_ADAPTER=playwright rednote-analyzer-mcp

Claude Desktop 配置（真实数据）：

{
  "mcpServers": {
    "rednote-analyzer-mcp": {
      "command": "uvx",
      "args": ["rednote-analyzer-mcp[browser]"],
      "env": {
        "REDNOTE_ADAPTER": "playwright",
        "REDNOTE_HEADLESS": "true"
      }
    }
  }
}

---

环境变量

变量	默认值	说明
REDNOTE_ADAPTER	mock	数据源：mock（模拟数据）或 playwright（真实浏览器）
REDNOTE_HEADLESS	true	浏览器模式：首次登录设为 false
REDNOTE_COOKIE_PATH	~/.rednote-mcp/cookies.json	Cookie 存储路径

---

开发

git clone https://github.com/ShellyDeng08/rednote-analyzer-mcp.git
cd rednote-analyzer-mcp
uv sync

# 代码检查
uv run ruff check src/

# 运行测试
uv run pytest

# MCP Inspector 测试
uv run mcp dev src/rednote_analyzer_mcp/server.py

---

合规说明

• 本项目不包含爬虫代码 — 浏览器适配器通过正常浏览获取公开内容
• 投资相关内容自动附带风险提示（⚠️ 投资有风险，本文不构成投资建议）
• 请遵守小红书用户协议和相关法律法规
• 模拟数据为虚构内容，仅供开发测试使用

License

MIT