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  1. Home
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  3. Analook — Competitor Intelligence
Analook — Competitor Intelligence logo
Health: ActiveRecent health check succeeded.Last checked 9/22/2026, 5:46:48 PM

Analook — Competitor Intelligence

User RatingsBe the first to rate and review this MCP server! Enrichment pendingWe haven’t run our AI enrichment pass on this listing yet, so the overview, use cases, and FAQ below may be sparse or missing. We work through the catalog over time — check back soon.
View Repository110 GitHub StarsTotal stargazers on GitHub for the source repository (110 stars).Visit Website

Competitor intelligence for AI agents — SEO, traffic, social, Product Hunt, pricing, AI insights.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.

Add to CursorAdd to VS Code
Manual Client & Custom JSON ConfigExpand JSON ▾

Client Config & Setup

Remote HTTP
Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "analook-competitor-intelligence": {
      "url": "https://www.analook.com/mcp"
    }
  }
}

💡 Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Directory Badge Claim listing Alternatives💰 More in Finance & Fintech

Documentation Overview

Analook Logo

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

License: MIT Website Skills on ClawHub Deployed on Railway

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.

config.json
{
  "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

  • 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)

SessionPriceBest For
Quick Call (30 min)$150 USDSpecific questions, quick diagnosis
Deep Dive (60 min)$300 USDFull strategy review, detailed roadmap

2. Advisory Retainer

PlanPriceIncludes
Monthly Retainer$1,500 USD/moUp to 5 hours strategic consultation + milestone reviews

3. Playbooks & Templates

PackagePriceContents
Starter Pack$29 USDCore methodology + essential tools
Flagship Bundle$199 USDComplete 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

SignalWhat You Learn
🌐 Website HistoryWhen launched, how fast it grew, Wayback timeline
📈 Traffic & SEOMonthly visits, top channels, keyword gaps
🐦 Twitter / XFollowers, engagement rate, content strategy
🚀 Product HuntLaunch scores, positioning, community response
💡 AI Deep DiveICP, business model, growth flywheel, tactical recs
📡 PropagationPeak traffic events, viral moments, channel breakdown
🧠 Growth StrategyEarly-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 gating
  • modules/ — 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 campaigns
  • static/ — the web UI served at analook.com
  • tests/ + 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

ModuleFileDescription
Website Historymodules/website_history.pyWayback Machine CDX API, first-seen date, snapshot timeline
Traffic & SEOmodules/traffic_analysis.pyDataForSEO — monthly visits, channels, top pages, keywords
Social Mediamodules/social.pyApify Twitter scraper — followers, engagement, recent content
Product Huntmodules/producthunt.pyPH GraphQL API — launches, scores, upvotes, reviews
OSS Growth Attributionmodules/oss_growth_attribution.pyGitHub star stages, public channel evidence, representative content links, confidence scoring
Growth Analysismodules/growth_analysis.pyTraffic peak detection, event correlation, growth stage
AI Summarymodules/ai_summary.py7-section structured analysis via TeamoRouter + DeepSeek fallback
Report Builderapp.pyFastAPI orchestrator — parallel pipeline, job state, streaming

🧠 AI Insights Depth

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

  1. 产品定位与 ICP — Target user profiles, market positioning, who actually pays
  2. 商业模式拆解 — Pricing model, conversion hypothesis, revenue estimate range
  3. 增长密码 — 4–6 data-backed growth strategies with evidence
  4. 增长飞轮 — Product-specific flywheel reconstruction
  5. 内容与传播策略 — Channel mix, content types, launch propagation model
  6. 给后来者的战术建议 — 5 actionable recommendations you can execute this week
  7. 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

bash
git clone https://github.com/Gingiris-1031/Competitor-analysis-tool.git
cd Competitor-analysis-tool
pip install -r requirements.txt

Create a .env file:

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

Run locally:

bash
uvicorn app:app --reload --port 8000

Visit 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:

bash
python3 scripts/verify_deploy_source.py

The 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:

Deploy on Railway

Steps:

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

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


🔌 API Integrations

ServicePurposeNotes
TeamoRouterPrimary LLMRoutes to best available model
DeepSeekFallback LLMCost-efficient backup
DataForSEOTraffic & SEO dataMonthly visits, channels, keywords
ApifyTwitter/X scrapingapidojo/twitter-profile-scraper actor
ProductHuntLaunch historyPH GraphQL API
Wayback MachineWebsite historyCDX 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?

Read the full README →View source on GitHub →

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Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars
110
Stargazers on the source repository.
Last commit
3d ago
Most recent push to the default branch.

Reviews

No reviews yet — be the first to share how this listing worked for you.

Frequently Asked Questions about Analook — Competitor Intelligence

Analook — Competitor Intelligence is a hosted MCP server. Add it as a remote server in your client's config: "mcpServers": { "analook-competitor-intelligence": { "url": "https://www.analook.com/mcp" } }

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Technical Specs & Signals

Category💰Finance & Fintech
More technical detailsExpand ▾
TransportSSE (Remote)
Last updatedSep 21, 2026
15/15 checks healthy over the last 45d
Views0
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Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars110
GitHub Star CountTotal stargazers on GitHub representing community popularity (110 stars).
Last commit3d ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Sep 21, 2026
45Quality signal: Fair · 45/100How this signal is calculated ▾
Server availabilityNot measured

Not scored for repo-hosted servers — we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools16/30
Adoption & activity8/15
Community engagement0/10

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