Best CLI Tools for Scheduling Social Media Posts (2026)

Most social media CLIs can schedule posts. You give them content, a date, and a platform. They handle the rest.

The difference is whether they can generate the content they schedule, or only schedule content you create elsewhere.

1. ReelsFarm CLI

ReelsFarm CLI generates content and schedules it in the same workflow.

The agent creates a TikTok slideshow with `reelsfarm slideshows prepare`. It builds the slides, adds hooks, sets the music timing. Then it schedules the post for a specific date and time. The prepare-then-confirm pattern means the draft sits in the queue until you approve it.

Scheduling is built into the content creation flow. You do not generate in one tool and schedule in another. The CLI handles both steps. The agent can prepare a week of content, you review the batch, and posts go live on schedule.

Support for recurring automations lets you set up a repeating slideshow schedule. Define the product, the format, and the frequency. The agent creates and schedules on the defined cadence.

Platforms: TikTok, Instagram, YouTube, Facebook.

2. Postiz CLI

Postiz CLI schedules posts across 28 platforms with OAuth2-connected accounts.

The scheduling is reliable and covers the widest platform set of any CLI. You provide content, pick platforms, set a date, and Postiz handles the rest. The JSON output makes it easy for AI agents to consume scheduling confirmations.

Postiz does not generate content. You schedule content you already have. For text and image posts across many platforms, the scheduling workflow is solid. For video or UGC content, you still need to create it first.

3. Taisly Agent Kit

Taisly schedules video posts across short-form platforms. TikTok, Instagram Reels, YouTube Shorts, X, Facebook.

The scheduling workflow includes video validation. Taisly checks platform requirements before scheduling. Aspect ratio, length, format. If the video does not meet platform specs, the agent knows before the scheduled time.

Taisly does not generate video. It validates and schedules video files you provide. The validation step is useful for video scheduling specifically because platform requirements vary.

4. SocialClaw

SocialClaw schedules posts across 11 platform families with a CLI, MCP server, API, and dashboard interface.

The scheduling workflow is validation-first. Its current MCP tools let an agent inspect account capabilities, upload media, preview and validate a campaign, apply a schedule, and inspect the resulting posts and delivery attempts. The dashboard lets you visually review the queue and analytics.

SocialClaw's hosted dashboard also includes a native drafting agent and a beta generator for turning app screenshots or screen recordings into UGC-style videos and photo carousels. Its [documented CLI and MCP surfaces](https://getsocialclaw.com/mcp) remain focused on publishing rather than exposing those media-generation features as agent tools. That makes it a strong scheduler with optional creation inside the dashboard.

5. Typefully CLI

Typefully CLI schedules text posts across X, LinkedIn, Threads, Bluesky, and Mastodon.

The scheduling handles thread formatting well. Threads are multiple posts that need to go out in sequence with correct reply chaining. Typefully manages this across platforms.

Text only. No video scheduling. No image scheduling beyond basic media attachments. But for text-first platforms, the thread scheduling is the best in this list.

Scheduling vs Generating

Scheduling is the easy part of social media automation. Every CLI in this list can schedule posts reliably.

The hard part is having something worth scheduling.

If you already produce content through another pipeline, any of these CLIs will schedule it. Pick based on platform coverage and agent integration preferences.

If you want your AI agent to generate specialized UGC assets and schedule them without moving into a separate dashboard, ReelsFarm CLI combines those steps in one agent-facing workflow. SocialClaw can also create selected content formats, but its current documentation places that generation experience in the hosted dashboard rather than the CLI or MCP toolset.