Analook
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.tools — Iris 的出海增长咨询,1:1 指导、开源项目运营、企业顾问服务
Table of Contents
🌱 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
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 |
What's Inside
This repo is the production backend powering analook.com:
app.py— FastAPI orchestrator: parallel analysis pipeline, job state, streaming, credit gatingmodules/— analysis engines (traffic, social, Product Hunt, growth analysis, AI summary) plus the Supabase client, payment integrations, and the MCP server (mcp_app.py)migrations/— Supabase SQL migrations (auth/credits/promo codes/attribution)scripts/— operational tooling: user metrics, attribution reports, EDM campaignsstatic/— the web UI served at analook.comtests/+Dockerfile— regression suite and container build
Stack: FastAPI + Supabase (auth, credits, report storage), deployed via Docker.
🔗 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 |
| Wayback Machine CDX API, first-seen date, snapshot timeline |
Traffic & SEO |
| DataForSEO — monthly visits, channels, top pages, keywords |
Social Media |
| Apify Twitter scraper — followers, engagement, recent content |
Product Hunt |
| PH GraphQL API — launches, scores, upvotes, reviews |
OSS Growth Attribution |
| GitHub star stages, public channel evidence, representative content links, confidence scoring |
Growth Analysis |
| Traffic peak detection, event correlation, growth stage |
AI Summary |
| 7-section structured analysis via TeamoRouter + DeepSeek fallback |
Report Builder |
| 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
Powered by TeamoRouter (primary) and DeepSeek (fallback), with max 4,000 token output per report.
⚡ Quick Start
git clone https://github.com/Gingiris-1031/Competitor-analysis-tool.git
cd Competitor-analysis-tool
pip install -r requirements.txtCreate 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 8000Visit http://localhost:8000
🚀 Deploy Your Own
Production source-of-truth
The production source is the main branch of
Gingiris-1031/Competitor-analysis-tool. Before any production deploy, run:
python3 scripts/verify_deploy_source.pyThe preflight fails if the checkout is behind origin/main, is on the wrong
branch or remote, or is missing tracked SEO/GEO assets such as
static/llms.txt, static/robots.txt, and static/sitemap.xml. This prevents
an older local clone from silently removing live assets during deployment.
The current production Fly app is declared in fly.toml as
competitor-analysis-tool. Run the preflight from the same checkout immediately
before fly deploy.
Self-hosting
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 |
Primary LLM | Routes to best available model | |
Fallback LLM | Cost-efficient backup | |
Traffic & SEO data | Monthly visits, channels, keywords | |
Twitter/X scraping |
| |
Launch history | PH GraphQL API | |
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.tools
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 |
⭐ 开源增长归因 | GitHub API + 公开内容检索 | Star 阶段、渠道证据、关键内容原链、证据置信度 |
💡 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
git clone https://github.com/Gingiris-1031/Competitor-analysis-tool.git
cd Competitor-analysis-tool
pip install -r requirements.txt
# 配置 .env 文件后:
uvicorn app:app --reload --port 8000Railway 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.tools
Telegram:@Iris_carrot
Twitter:@WeiYipei
License
MIT — free to use, modify, and redistribute.
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