How do I install Analook — Competitor Intelligence?

Copy the http config for Cursor, Claude Desktop, Claude Code, or VS Code on this page. It uses the publisher's install, not a PlugMCP proxy.

Does Analook — Competitor Intelligence need an API key?

No required environment variable is listed on this record.

What transport does Analook — Competitor Intelligence use?

Analook — Competitor Intelligence is reached over HTTP.

When was Analook — Competitor Intelligence last checked?

Last checked 2026-11-09. Competitor intelligence for AI agents — SEO, traffic, social, Product Hunt, pricing, AI insights.

Analook — Competitor Intelligence MCP server

Power your agent

Add this server

The publisher's own URL. Not a PlugMCP endpoint.

Add to Cursor Add in Claude Add to VS Code Run on PlugMCP

Host a copy with our keys and logs.

Server URL

https://www.analook.com/mcp

The Claude button above opens Claude with the name and URL filled in. You still confirm it there.

shClaude Code

1claude mcp add --transport http io.github.gingiris-analook https://www.analook.com/mcp

Run in a terminal.

jsonClaude Desktop

1{2  "mcpServers": {3    "io.github.gingiris-analook": {4      "command": "npx",5      "args": [6        "-y",7        "mcp-remote",8        "https://www.analook.com/mcp"9      ]10    }11  }12}

claude_desktop_config.json

Remote · HTTPPublisher installStep-by-step: add this in Claude

Remote URL or a command on your machine? How the two installs differ

Run on PlugMCP

Host a copy with our keys and logs.

A new server you create. It is not this listing's official endpoint. Use the publisher install when you want their URL and their credentials.

Launch

Server facts

Live

Transport: http
Version: 1.0.0
Last checked

8 tools

Tools

tools/listVoice mode preview

Tool	What it does
analyze_competitor	Submit a competitor analysis job. Analyzes a competitor's website across 15+ data sources (SEO, traffic, social, Product Hunt, GitHub, Wayback Machine history, AI-generated insights, etc.) and returns a job_id. Use get_report_status(job_id) to poll and get_report(job_id) to retrieve
get_report_status	Poll an analysis job's status. Args: job_id: ID returned from analyze_competitor() Returns: {status: 'running'\|'completed'\|'failed', progress?: str, report_url?: str}
get_report	Fetch the full competitor analysis report as structured JSON. Reports contain: website snapshot, Wayback Machine history, SEO/traffic data (DataForSEO), social media presence, Product Hunt launches, GitHub stats, pricing, funding, AI-generated business insights, growth playbooks, an
get_report_markdown	Fetch the competitor analysis report as human-readable Markdown. Suitable for piping into agents that prefer text over structured JSON, or for direct display to end users. Args: job_id: ID from analyze_competitor(); status must be 'completed' Returns: {markdown: st
list_my_reports	List your recent competitor analysis reports (up to 50). Requires authentication. Returns a lightweight list (id, url, product_name, created_at, status) — use get_report(job_id) to fetch the full report for any of them. Returns: {reports: [{id, url, product_name, created_at
run_growth_audit	Run a full Growth Audit — three linked strategic reports for a product. Unlike analyze_competitor (a single 15-signal intelligence snapshot), a Growth Audit produces an Executive Summary + a Diagnosis Report + a 30-day Action Plan, grounded in real channel/tactic playbooks. Best for 'ho
get_growth_audit	Fetch a Growth Audit's three reports (Executive Summary, Diagnosis, Action Plan) as Markdown. Args: job_id: ID from run_growth_audit() (starts with 'ga-') Returns: {status, reports: {executive_summary, diagnosis_report, action_plan}} while running, only {status,
browse_public_reports	Browse Analook's public competitor-intelligence report gallery. Returns recently published public reports (product name, domain, category, and a link). No authentication or credits required — a fast way to discover existing analyses before spending a credit on a fresh one. Args:

Analook — 竞品情报分析工具

30 秒看透任何竞品 · AI-powered competitor intelligence for indie hackers & growth teams

English | 中文 · 🤖 MCP Server · 📖 Docs

🤖 Remote MCP Server

Analook is available as a Remote MCP server — use it from Claude Desktop, Cursor, or any MCP-compatible client. No install, no local process.

{
  "mcpServers": {
    "analook": {
      "url": "https://www.analook.com/mcp",
      "headers": { "Authorization": "Bearer <YOUR_ANALOOK_TOKEN>" }
    }
  }
}

5 tools: analyze_competitor, get_report_status, get_report, get_report_markdown, list_my_reports.

Full docs & token instructions → analook.com/docs/mcp

💡 出海增长咨询 · 1v1 Session 约课 $200 — Telegram @Iris_carrot

或访问 gingiris.com — Iris 的出海增长咨询，1:1 指导、开源项目运营、企业顾问服务

What is Analook
Live Demo
Analysis Modules
AI Insights Depth
Quick Start
Deploy Your Own
API Integrations
Work With Iris
About the Author
中文版

🌱 Philosophy

"做竞品分析不是为了抄，是为了找到别人没做好的地方。" — Competitor research isn't about copying — it's about finding the gaps they left open.

"数据会说话，但你得先知道问对问题。" — Data speaks, but only if you ask the right questions.

"30 秒看懂一个产品，30 天超越它。" — Understand a product in 30 seconds. Surpass it in 30 days.

💼 Work With Iris

1. Strategic Consultation (1v1)

Session Price Best For
Quick Call (30 min) $150 USD Specific questions, quick diagnosis
Deep Dive (60 min) $300 USD Full strategy review, detailed roadmap

2. Advisory Retainer

Plan Price Includes
Monthly Retainer $1,500 USD/mo Up to 5 hours strategic consultation + milestone reviews

3. Playbooks & Templates

Package Price Contents
Starter Pack $29 USD Core methodology + essential tools
Flagship Bundle $199 USD Complete SOP, competitor research framework, templates

📩 Contact @Iris_carrot on Telegram — Crypto/USDT and Wire Transfer accepted

Session	Price	Best For
Quick Call (30 min)	$150 USD	Specific questions, quick diagnosis
Deep Dive (60 min)	$300 USD	Full strategy review, detailed roadmap

Plan	Price	Includes
Monthly Retainer	$1,500 USD/mo	Up to 5 hours strategic consultation + milestone reviews

Package	Price	Contents
Starter Pack	$29 USD	Core methodology + essential tools
Flagship Bundle	$199 USD	Complete SOP, competitor research framework, templates

What is Analook?

Analook is an open-source AI-powered competitor intelligence tool built by Iris, former cofounder & COO of AFFiNE (60k+ stars).

Enter any product URL. In ~30 seconds, Analook runs a 7-module parallel analysis pipeline and returns a structured deep-dive report — growth strategy, traffic signals, social footprint, ProductHunt history, AI insights, and more.

Built for:

Indie hackers validating a market before building
Growth teams benchmarking against competitors
Investors doing quick pre-DD intelligence
Founders preparing a launch in a crowded niche

Analysis Results Include

Signal	What You Learn
🌐 Website History	When launched, how fast it grew, Wayback timeline
📈 Traffic & SEO	Monthly visits, top channels, keyword gaps
🐦 Twitter / X	Followers, engagement rate, content strategy
🚀 Product Hunt	Launch scores, positioning, community response
💡 AI Deep Dive	ICP, business model, growth flywheel, tactical recs
📡 Propagation	Peak traffic events, viral moments, channel breakdown
🧠 Growth Strategy	Early-stage strategy reconstruction from public signals

🔗 Live Demo

analook.com — Free to use. No login required.

Try with: lovable.dev · linear.app · notion.so · cursor.com

📦 Analysis Modules

Module	File	Description
Website History	`modules/website_history.py`	Wayback Machine CDX API, first-seen date, snapshot timeline
Traffic & SEO	`modules/traffic_analysis.py`	DataForSEO — monthly visits, channels, top pages, keywords
Social Media	`modules/social.py`	Apify Twitter scraper — followers, engagement, recent content
Product Hunt	`modules/producthunt.py`	PH GraphQL API — launches, scores, upvotes, reviews
Growth Analysis	`modules/growth_analysis.py`	Traffic peak detection, event correlation, growth stage
AI Summary	`modules/ai_summary.py`	7-section structured analysis via TeamoRouter + DeepSeek fallback
Report Builder	`app.py`	FastAPI orchestrator — parallel pipeline, job state, streaming

🧠 AI Insights Depth

Analook's AI module goes beyond surface-level summaries. Each report includes:

产品定位与 ICP — Target user profiles, market positioning, who actually pays
商业模式拆解 — Pricing model, conversion hypothesis, revenue estimate range
增长密码 — 4–6 data-backed growth strategies with evidence
增长飞轮 — Product-specific flywheel reconstruction
内容与传播策略 — Channel mix, content types, launch propagation model
给后来者的战术建议 — 5 actionable recommendations you can execute this week
风险与机会 — Red flags and market gaps, with data citations

⚡ Quick Start

# Source available at https://clawhub.ai/user/gingiris
# (Skills published under @gingiris; contact [email protected] for source code access)
cd Competitor-analysis-tool
pip install -r requirements.txt

Create a .env file:

TEAMOROUTER_API_KEY=sk-teamo-...
DEEPSEEK_API_KEY=sk-...
DATAFORSEO_B64=base64(email:password)
PRODUCTHUNT_TOKEN=...
APIFY_API_TOKEN=apify_api_...

Run locally:

uvicorn app:app --reload --port 8000

Visit http://localhost:8000

🚀 Deploy Your Own

One-click deploy on Railway:

Steps:

Fork this repo
Create a new Railway project → connect your fork
Add the environment variables above in Railway → Settings → Variables
Railway auto-deploys on every push to main

The app is Dockerized and uses Nixpacks on Railway (Python 3.13).

🔌 API Integrations

Service	Purpose	Notes
TeamoRouter	Primary LLM	Routes to best available model
DeepSeek	Fallback LLM	Cost-efficient backup
DataForSEO	Traffic & SEO data	Monthly visits, channels, keywords
Apify	Twitter/X scraping	`apidojo/twitter-profile-scraper` actor
ProductHunt	Launch history	PH GraphQL API
Wayback Machine	Website history	CDX API + timemap

⭐ Star This Repo

If Analook saved you hours of manual research, a ⭐ helps others discover it!

About the Author

Iris (生姜iris) — Former cofounder & COO of AFFiNE (60k+ GitHub stars). Now running Gingiris — an open-source go-to-market and global expansion consulting practice.

🐦 Twitter: @WeiYipei
💬 Telegram: @Iris_carrot
🌐 Website: gingiris.com

Related Playbooks (now on ClawHub):

@gingiris on ClawHub — GTM strategy, B2B SaaS PLG/SLG growth, open source launch marketing, and other AI-agent skills

中文版

Analook 是什么？

Analook 是一个开源 AI 竞品情报工具，由 AFFiNE（60k+ stars）联创 & 前 COO Iris 构建。

输入任意产品网址，30 秒内生成一份结构化竞品深度报告——包含增长策略、流量信号、社交足迹、ProductHunt 历史、AI 洞察等全套数据。

适合谁用？

独立开发者 — 开始动手前快速验证市场
增长团队 — 对标竞品，找到差距
投资人 — Pre-DD 快速情报收集
创始人 — 在红海市场找到进攻角度

核心分析模块

模块	数据来源	输出内容
🌐 网站历史	Wayback Machine	上线时间、成长速度、快照时间线
📈 流量 & SEO	DataForSEO	月访问量、流量渠道、关键词矩阵
🐦 Twitter/X	Apify	粉丝数、互动率、内容策略
🚀 Product Hunt	PH GraphQL	发布记录、评分、社区反馈
💡 AI 深度分析	TeamoRouter	ICP 画像、商业模式、增长飞轮、战术建议
📡 传播分析	综合	流量峰值事件、渠道来源、传播节点
🧠 早期增长策略	综合	从公开信号反推产品早期增长路径

快速部署

# Source: https://clawhub.ai/user/gingiris  (联系 [email protected] 获取源代码访问)
cd Competitor-analysis-tool
pip install -r requirements.txt
# 配置 .env 文件后：
uvicorn app:app --reload --port 8000

Railway 一键部署： Fork 本 repo → Railway 连接 → 添加环境变量 → 自动部署 ✅

关于作者

Iris（生姜iris），AFFiNE 联创 & 前 COO，现运营 Gingiris 开源出海增长咨询。

出海咨询预约：gingiris.com
Telegram：@Iris_carrot
Twitter：@WeiYipei

Analook — Competitor Intelligence

Add this server

Host a copy with our keys and logs.

Server facts

Tools

Questions

How do I install Analook — Competitor Intelligence?

Does Analook — Competitor Intelligence need an API key?

What transport does Analook — Competitor Intelligence use?

When was Analook — Competitor Intelligence last checked?

Documentation

Analook — 竞品情报分析工具

30 秒看透任何竞品 · AI-powered competitor intelligence for indie hackers & growth teams

🤖 Remote MCP Server

Table of Contents

What is Analook?

Analysis Results Include

🔗 Live Demo

📦 Analysis Modules

🧠 AI Insights Depth

⚡ Quick Start

🚀 Deploy Your Own

🔌 API Integrations

⭐ Star This Repo

About the Author

中文版

Analook 是什么？

适合谁用？

核心分析模块

快速部署

关于作者