10 free github repos that can replace major SaaS with subscriptions.
all free. open-sourced. some are MIT licensed.
—
1️⃣ openscreen — replaces screen studio ($29/mo)
- a clean macOS/windows/linux screen recorder for polished demos.
- blur, cursor highlighting, annotations, export to mp4 or gif at any aspect ratio.
- doesn't try to clone every feature, just nails the basics for quick walkthroughs you'd post on X.
—
2️⃣ voicebox — replaces elevenlabs ($22/mo) + wisprflow ($15/mo)
- local-first AI voice studio.
- clone voices from 3 seconds of audio, generate speech across 7 TTS engines in 23 languages,
- dictate into any text field with a global hotkey.
- nothing leaves your machine.
- runs on apple silicon, cuda, rocm.
—
3️⃣ openshorts — replaces opus clip ($19/mo) + submagic ($16/mo)
- free AI video platform.
- clip generator turns long youtube videos into 9:16 shorts with auto-subtitles and face tracking (runs on free gemini + elevenlabs tiers).
- also includes AI UGC video generation with actors — that part is pay-per-use via fal. ai (~$0.65-2 per video). docker self-host.
—
4️⃣ freellmapi — replaces chatgpt pro + claude pro ($20/mo each)
- stacks 14 free AI provider tiers (google, groq, cerebras, openrouter, github models + 9 more) behind one openai-compatible endpoint.
~800M tokens/month.
- smart router with failover, sticky sessions, encrypted key storage. ships with a dashboard.
—
5️⃣ playwright-mcp — replaces browserbase ($39/mo) + browser use ($25/mo)
- microsoft's official MCP server that gives any AI agent full browser control.
- uses accessibility trees, not screenshots — deterministic and token-efficient.
- works with claude code, cursor, windsurf, codex out of the box.
—
6️⃣ vibe-trading — replaces tradingview premium ($60/mo)
- natural-language finance research agent.
- 7 backtest engines across stocks, crypto, futures, forex.
- 75 specialist skills (factor analysis, options strategy, ML strategy).
- 29 multi-agent swarm presets.
- 21 of 22 MCP tools work with zero API keys.
—
7️⃣ CalCom — replaces calendly ($12/mo) + savvycal ($12/mo)
- the open-source scheduling infrastructure.
- one-on-ones, group events, round-robin, team booking,
- payment collection (stripe), routing forms, workflows.
- integrates with google/outlook/apple calendar, zoom, meet, teams.
- self-host in 10 minutes with docker. 40k stars.
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8️⃣ whisper — replaces otter ($17/mo)
- openAI's open-source speech-to-text model.
- transcribe audio in 99 languages, translate to english, generate timestamps.
- runs locally on cpu or gpu.
- the actual model behind most "AI transcription" SaaS tools you're paying for.
—
9️⃣ postiz — replaces buffer ($15/mo)
- AI-powered social media scheduler.
- cross-post to X, linkedin, instagram, tiktok, threads, bluesky, mastodon, youtube, pinterest.
- AI captions and hashtags.
- analytics dashboard. team workspaces. 31k stars and rising.
—
🔟 vaultwarden — replaces 1password ($8/mo)
- unofficial bitwarden-compatible server written in rust.
- works with every official bitwarden client (mobile, desktop, browser).
- unlimited users, unlimited vaults, full enterprise feature set.
- runs on a $5 VPS or your home server.
—
disclaimer:
open-source ≠ 1:1 replacement. you'll trade polish for ownership, hand-holding for control, and a credit card for a github version.
for builders, prototypers, and indie hackers — that's the whole point.
for everyone else, the paid tools still have their place.
bookmark this. share with one friend bleeding subscription fees.
~m0h
Claude 팀이 30분 이내에 AI 에이전트 만드는 방법공개
요즘 Ai 바이브 코딩을 하다보니까
이런 강의가 정말 필요했는데 찾아보니
클로드 팀이 직접 강의 한게 있어서 가져와봄
원본 24분이고 한국어로 핵심 요약해서
10분정도로 편집해봤습니다
영상보고 풀버전 궁금하신분은
댓글에 출처와 원본 남겨놓겠습니다 !
the fastest growing GitHub repos in finance this week:
1. TradingAgents (+3,822 ★)
multi-agent LLM trading framework built for financial research and execution. combines analyst agents, sentiment models, portfolio reasoning, and provider integrations into a single trading stack.
2. AI-Trader (+2,434 ★)
fully automated agent-native trading system. built around autonomous decision-making, price fetching, execution, and monitoring workflows. focused on end-to-end AI-driven trading infrastructure.
3. scientific-agent-skills (+2,286 ★)
plug-and-play agent skills for finance, research, science, engineering, and writing. integrates with multiple agent frameworks and supports web research, bioinformatics, cheminformatics, and analysis pipelines.
4. daily_stock_analysis (+1,272 ★)
LLM-powered stock analysis platform covering US, Hong Kong, and Chinese equities. combines market data, real-time news, AI dashboards, automated reporting, and multi-channel notifications with near-zero operating cost.
5. QuantDinger (+1,242 ★)
AI quantitative trading platform for crypto, stocks, and forex. includes live trading, strategy backtesting, market analytics, and broker integrations. built for traders experimenting with AI-assisted quant workflows.
6. Vibe-Trading (+1,148 ★)
personal AI trading agent focused on algorithmic trading and backtesting. combines lightweight automation with agent-style portfolio management and strategy experimentation.
7. FinceptTerminal (+878 ★)
modern open-source finance terminal inspired by Bloomberg-style workflows. provides market analytics, investment research, trading tools, and AI-powered financial infrastructure in one interface.
8. TradingAgents-CN (+739 ★)
Chinese-enhanced version of TradingAgents. adapts the multi-agent LLM trading framework for Chinese financial markets, datasets, and workflows. rapidly growing among Chinese quant and AI communities.
9. last30days-skill (+694 ★)
AI agent skill for researching trends across Reddit, X, YouTube, Hacker News, Polymarket, and the broader web. designed for signal discovery, narrative tracking, and internet-wide monitoring.
10. qlib (+680 ★)
Microsoft’s AI-oriented quant investment platform. covers the entire quant pipeline from data collection to alpha generation, portfolio construction, and execution. still one of the strongest open-source quant ecosystems available.
bookmark this and start today.
매달 나가는 VPN 구독료 아까우면서 정작 직접 띄울 생각은 안 하던 사람들 뒤통수 때리는 오픈소스임. 25KB짜리 DSVPN 라이브러리에 명령어 두 줄이면 5달러짜리 가상 서버 하나로 평생 무료 VPN 망이 깔림. 대기업 보안 솔루션 부럽지 않게 내 인프라 내가 통제하면서 고정비 제어로 묶어버리는 게 진짜 실전 엔지니어링임.
맨날 네네거리는 조수 말고 내 아이디어에 태클 걸고 성과까지 추적하는 '인격'을 심는 법임. 170줄짜리 마크다운 파일 하나로 에이전트의 뇌 구조를 단순 비서에서 운영 파트너로 통째로 갈아 끼우는 게 소름 돋네. 비위 맞추는 AI는 이제 지겨우니 진짜 일할 놈이 필요하면 이 구조부터 뜯어보자.
중국 애들이 이번엔 로컬에서 24시간 자율로 돌아가는 에이전트를 오픈소스로 풀었음. 코딩부터 영상 제작까지 지 혼자 다 한다는데, 클라우드 종속성 없이 내 컴퓨터 자원만 써서 이 정도 생산성 뽑아내면 에이전트 시장 판도 자체가 바뀔 듯. API 비용 걱정 없이 무한 동력으로 돌릴 수 있다는 게 가장 무서운 포인트임.
다들 로컬 AI 모델 구성 시작하실때 lm studio 에서 unsloth/gemma-4-26B-A4B-UD-IQ2-XXS 로 해보세요, 램이 10GB 이상만 있으면 잘 동작합니다. 초당 40 에서 50 tps 나오니 소넷 정도에게 맡기려던 에이전트 작업은 로컬 모델로 시작해보면 로컬 모델 시작하기 너무 좋습니다...!
this chinese developer making $320k/year as a solo contractor
his secret: 5 AI agents running in parallel, each one a specialist
architect, coder, reviewer, tester, ops
they don’t share context, don’t step on each other, just ship
he takes on projects meant for teams of 5-8 engineers
delivers in half the time
keeps the entire budget
found this video on bilibili at 3am and watched it four times
guy sitting at his desk, two monitors filled with code, and he’s barely touching the keyboard
here’s what’s happening on his screen:
> agent 1 (architect): designs system structure, breaks down features into tasks, decides what gets built first
> agent 2 (coder): writes the actual implementation based on architect’s specs
> agent 3 (reviewer): checks every piece of code for bugs, edge cases, security issues
> agent 4 (tester): generates test cases, runs them, reports failures back
> agent 5 (ops): handles deployment, monitoring, infrastructure
five separate claude code instances running simultaneously
each one has its own system prompt, its own context, its own specialty
they communicate through a shared task queue, not through each other
that’s the key insight - no shared context means no conflicts
agent 2 doesn’t know what agent 3 is doing
agent 4 doesn’t care what agent 1 decided
they just pick up tasks, complete them, move on
he showed his contract history:
> 3D rendering pipeline for a gaming studio: $25k
> automated trading dashboard: $33k
> enterprise CRM rebuild: $44k
all completed solo, all delivered early, all clients thought they were hiring a team
the code on his screen is python with blender integration - complex stuff that would normally require 3-4 specialists
he’s shipping it in days while the client expects weeks
while he’s explaining the system to camera, commits are happening in the background, tests running, deployments going out
all while he’s literally not touching the keyboard
his API costs run about $2k/month
his revenue averages $26k/month
that’s a 13x return on his AI investment
this is the new solo developer playbook
don’t compete with teams
become the team
API 1만 개를 한곳에 모아놨다니 이건 거의 개발자용 치트키 수준임. 단순히 많은 게 아니라 당장 서비스에 꽂아서 쓸 수 있는 것들이라 활용도가 미쳤음. 자동화든 서비스 구축이든 일단 여기서 도구부터 챙기고 시작하는 게 지름길임. 남들 삽질할 때 리스트 한 번 훑어보는 게 진짜 실력이라고 봄 ㅋㅋㅋ