PostEverywhere is a social media scheduling and management tool built around posting across multiple networks from one place. It lets users upload content once, schedule it, and distribute it across 11 platforms, with support for Instagram, LinkedIn, TikTok, Facebook, X, YouTube, Threads, Bluesky, Telegram, Discord, and Pinterest. The service also describes itself as an all-in-one platform for social media workflows.
Its feature set includes a visual drag-and-drop content calendar, cross-platform publishing, AI automation for posting at optimal times, and AI content generation for captions, images, and videos. It supports bulk scheduling through CSV upload, manages up to 40 accounts, and provides analytics for tracking performance across platforms. The site also says it can generate platform-optimized captions in a brand voice and create images and short-form videos with named AI models and tools.
PostEverywhere is also designed to work with AI agents. It says Claude, ChatGPT, Codex, Cursor, Hermes, OpenClaw, and Windsurf can connect through a single URL, and that tasks such as scheduling, generating captions and images, retrying failures, reading analytics, and managing webhooks can be called in plain language. The same page mentions a REST API, an SDK, API docs, free tools, how-to guides, and a help center. It names agencies as users needing multi-client management at scale and creators as users who want to grow their audience.
No license is stated.
PostEverywhere is a Marketing & ads project. It focuses on automating and managing multi-platform social media posting and scheduling from a single interface or via API/CLI. It is built as a B2B product for social media managers and developers. There is a free tier, and paid plans start at $19. PostEverywhere is available on the web, the command line, and API.
PostEverywhere first shipped in 2026. The project is developed in the open on GitHub with 8 commits in the last 90 days. Key capabilities include social media scheduler, content calendar, and bulk scheduling. It exposes integrations via an MCP server and a public API.
Summary written by a language model from the project’s public pages.
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