Abstract
Free AI Social Media Scheduler is an open-source Digital Marketing & SEO project. Free open-source AI social media scheduler — self-hostable alternative to Postiz, Buffer, and Hootsuite with built-in AI content generation. A free, open-source AI social media scheduler built with Next.js. Upload videos, schedule posts, and publish directly to YouTube and TikTok — no subscription required. It is built using JavaScript, Next.js. Key capabilities include: AI Social Marketing Agent (/agents) — conversational AI marketing assistant with persistent context memory across conversations:; 3-Panel Workspace — multi-channel selector on the left, interactive chat in the center, and conversation history threads on the right; Platform-Tailored Copy — generates viral hooks, high-converting captions, and hashtag strategies tailored to specific character limits and algorithms. The complete source code is publicly available on GitHub under the MIT License, making it a useful reference for students building a Digital Marketing & SEO mini project or final-year project.
1. Introduction
A free, open-source AI social media scheduler built with Next.js. Upload videos, schedule posts, and publish directly to YouTube and TikTok — no subscription required. Self-hostable alternative to Buffer, Hootsuite, Later, and Sprout Social.
2. Objective
Free open-source AI social media scheduler — self-hostable alternative to Postiz, Buffer, and Hootsuite with built-in AI content generation.
This project demonstrates how JavaScript, Next.js can be applied to a real-world Digital Marketing & SEO problem.
3. Key Features / Modules
- AI Social Marketing Agent (/agents) — conversational AI marketing assistant with persistent context memory across conversations:
- 3-Panel Workspace — multi-channel selector on the left, interactive chat in the center, and conversation history threads on the right.
- Platform-Tailored Copy — generates viral hooks, high-converting captions, and hashtag strategies tailored to specific character limits and algorithms.
- 1-Click Post Proposals — prepares structured post cards ready to open in the Composer and schedule with one click.
- Rich Markdown Rendering — full typography with headings, styled bullet points, code blocks, and expandable JSON payloads.
- Context Memory — retains tone, campaign guidelines, and brand instructions across the last 10 messages.
- Video & Post Scheduling — upload media or paste a URL, pick target platforms and times, and publish automatically.
- Multi-Account Management — connect and manage multiple social accounts (YouTube, TikTok, X, LinkedIn) from a unified dashboard.
- YouTube Controls — category selection, privacy (public/private/unlisted), made-for-kids flags.
- TikTok Controls — privacy settings, comment, duet, and stitch toggles.
4. Technology Stack
- Framework: Next.js 16 (App Router + Turbopack)
- Auth: NextAuth.js (Google OAuth)
- Database: PostgreSQL + Prisma ORM
- Payments: Stripe
- AI / Publishing: MuAPI
- Markdown: react-markdown + remark-gfm
- Styling: Tailwind CSS + Framer Motion
5. System Requirements
General requirements for this technology stack — check the README for exact versions.
- Node.js (LTS) and npm
- A modern web browser
- VS Code or any code editor
- Git (to clone the repository)
6. Installation & Setup
git clone https://github.com/Anil-matcha/Free-AI-Social-Media-Scheduler.git
cd Free-AI-Social-Media-SchedulerFull setup instructions are in the project README.
7. Future Enhancements
Suggested extensions you can add to make this your own project.
- Export reports to Google Sheets or PDF
- Schedule weekly automated reports
- Add competitor comparison
8. Viva / Review Questions
Common questions examiners ask for projects in this domain.
- Which marketing or SEO problem does this tool solve?
- Which data sources or APIs does it use (Search Console, Analytics, social platforms)?
- Which metrics or KPIs does it report and how are they calculated?
- How could the output help a business make decisions?
- How would you schedule it to run automatically?
9. Source Code & License
This project is developed by Anil-matcha and published on GitHub under the MIT License. Please follow the license terms and credit the original author when you use or modify this code.
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