MarketMeNow

The marketing intern that never sleeps.

Open-source framework that generates and publishes marketing content across 6 platforms from a single command.

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Marketing was eating 2+ hours/day as a solo founder. So I built myself an intern. After one week: 14k+ impressions, 700+ website visits, ~5 min/day of my time. (results on Gradeasy)

Click to watch an AI-generated Instagram Reel

Platform	Content	Generate	Publish	In-Context Learning
Instagram	Reels, Carousels	✅	✅	✅
X / Twitter	Replies, Threads	✅	✅	✅
Reddit	Comments, Posts	✅	✅	-
LinkedIn	Posts, Images, Videos, Docs	✅	🚧 WIP	-
YouTube	Shorts	✅	✅	-
Email	Bulk outreach	✅	✅	-

Features

In-Context Learning Learns from your top-performing posts. The more you post, the better it matches your voice.	Brand Templates Figma MCP + YAML templates. Your fonts, colors, layout. AI fills the content.	Engagement Automation Finds relevant conversations, writes contextual replies, posts with human-like timing.
Email Batching CSV in, 100 personalized emails out. Picks up where it left off.	Real-Time Dashboard Live progress, streaming logs, approve/reject per item. One click to publish all.	Modular Adapters Add a platform with zero changes to core. Ports-and-adapters architecture.

Quick Start

git clone https://github.com/thearnavrustagi/marketmenow.git && cd marketmenow && bash setup.sh

Edit .env with your API keys, then:

uv run mmn-web          # Dashboard at http://localhost:8000

Requirements: Python 3.12+, uv (setup.sh installs it). Docker recommended for PostgreSQL. Node.js 18+ only if you want Instagram Reels.

Manual setup

git clone https://github.com/thearnavrustagi/marketmenow.git
cd marketmenow

uv sync
docker compose up -d
cp .env.example .env

uv run playwright install chromium
cd src/adapters/instagram/reels/remotion && npm install && cd -

uv run mmn-web

Platform credentials

You only need credentials for the platforms you use:

Platform	What you need
Instagram	INSTAGRAM_ACCESS_TOKEN, INSTAGRAM_BUSINESS_ACCOUNT_ID
Twitter/X	TWITTER_AUTH_TOKEN, TWITTER_CT0 (or mmn auth twitter)
Reddit	REDDIT_SESSION cookie, REDDIT_USERNAME
LinkedIn	LINKEDIN_ACCESS_TOKEN (or LINKEDIN_LI_AT cookie)
YouTube	Google OAuth 2.0 (mmn auth youtube)
Email	SMTP_HOST, SMTP_PORT, SMTP_USERNAME, SMTP_PASSWORD, SMTP_FROM
AI (all)	GOOGLE_APPLICATION_CREDENTIALS, VERTEX_AI_PROJECT

CLI reference

# Workflows (primary interface)
mmn workflows                                    # List all workflows
mmn run instagram-reel --template can_ai_grade_this --tts kokoro
mmn run instagram-carousel
mmn run twitter-thread --topic "AI in marketing"
mmn run twitter-engage --headless --max-replies 10
mmn run reddit-engage --max-comments 5
mmn run reddit-launch -c campaigns/my-campaign.yaml -b blog-draft.md --dry-run
mmn run linkedin-post --count 3 --dry-run
mmn run email-outreach -t template.html --to [email protected]
mmn run youtube-short --video video.mp4 --title "My Short"

# Authentication
mmn auth twitter --cookies
mmn auth linkedin --oauth
mmn auth youtube

# Info
mmn workflows                          # List available workflows
mmn run <workflow> --info              # Detailed help for a workflow
mmn platforms                          # List supported platforms
mmn version                            # Show version

# Distribute pre-built content
mmn distribute -c content.json --only instagram,linkedin

Customizing for your brand

All brand identity lives in YAML files, not code. Repurpose the entire tool for your product in under an hour.

Prompts (text content: tweets, carousels, LinkedIn, Reddit, email):

1. Swap the brand (5 min): Open prompts/ and replace Gradeasy with your brand name, URL, and audience keywords.
2. Tweak the voice (10 min): Each prompt has a persona section. Edit the voice for each platform in prompts/<platform>/.
3. Adjust topics (5 min): Search for topic constraints and replace with your domain.
4. Set mention rate: Each prompt has a MENTION STRATEGY section controlling how often your brand appears.

Or use the meta-prompt in prompts/prompt.md to generate entire prompt YAML files with any AI chat.

Reels (video content):

The existing reels are purpose-built for Gradeasy's concept. For your product you'll want a completely different reel — different narrative, different scenes, different voice. The reel template meta-prompt in src/adapters/instagram/reels/templates/prompt.md lets you paste your brand details and reel concept into ChatGPT / Claude and get back both files you need:

1. A template YAML — the video structure (scenes, beats, transitions, pipeline)
2. A companion prompt YAML — the AI persona that writes the script

Drop them into src/adapters/instagram/reels/templates/ and prompts/instagram/, then run mmn reel create --template your_id. Full schema reference, available scenes, transitions, and pipeline steps are all in that file.

Architecture

Ports-and-adapters design. The core engine knows nothing about any specific platform. Each adapter implements PlatformAdapter, ContentRenderer, and Uploader protocols.

graph LR
    subgraph core [Core]
        direction TB
        Scheduler --> Orchestrator
        Orchestrator --> Pipeline
        Pipeline --> Normaliser
    end

    subgraph ports [Protocols]
        direction TB
        Renderer["ContentRenderer"]
        Uploader["Uploader"]
        Adapter["PlatformAdapter"]
    end

    subgraph adapters [Adapters]
        direction TB
        IG["Instagram"]
        TW["Twitter / X"]
        RD["Reddit"]
        LI["LinkedIn"]
        YT["YouTube"]
        EM["Email / SMTP"]
    end

    Pipeline --> Renderer
    Pipeline --> Uploader
    Pipeline --> Adapter
    IG -.-> Adapter
    TW -.-> Adapter
    RD -.-> Adapter
    LI -.-> Adapter
    YT -.-> Adapter
    EM -.-> Adapter

Pipeline: Normalise -> Render -> Upload -> Publish

Adding a platform: Create src/adapters/yourplatform/, implement the protocols, register with AdapterRegistry. Zero changes to core.

Roadmap

Checked items are shipped. Unchecked items are planned or in progress.

Done

• 6-platform content engine — Instagram Reels & Carousels, Twitter replies & threads, Reddit comments, LinkedIn posts, YouTube Shorts, bulk email — generate and publish from one CLI or web dashboard
• In-context learning & brand templates — learns from top-performing posts to match your voice; YAML-driven brand identity (prompts, visuals, mention strategy) with Figma MCP integration
• Ports-and-adapters core — modular pipeline (normalise → render → upload → publish), campaign orchestrator, scheduler, and AdapterRegistry — add a platform with zero changes to core

Up Next

• Reddit & LinkedIn publish — finish WIP uploaders for both platforms, full end-to-end tests
• Personas — bundle brand voice, visual identity, prompts, and platform credentials into switchable "personas" so you can manage multiple brands or collaborate with a team from one install
• Twitter discovery & cold DM — find Twitter accounts relevant to your brand, score them, and send personalized cold DMs at human-like pace
• Pipelines & modularisation — composable pipelines that chain the existing tools (discover → generate → review → publish) into reusable flows you define in YAML and execute with a single command

Star History

Contributing

See CONTRIBUTING.md for development setup, code style, and the PR process.

License

MIT