Social media decision

Schedule & Chill

A competent developer can build and self-host the core (REST API, MCP server, media, and scheduler) using existing open-source schedulers as prior art; the product’s value is reproducible and not protected by durable moats.

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Built by Zakir 🇧🇩, who ships 3 products in this index

You pay

Not priced

No pricing page we fetched carried a figure, so there is nothing to compare against. The build side is still real.

You’d pay instead

$100one-off60 h to build

$50/mo6 h/mo upkeep

No published price to break even against.

Open-source builds that already do this

Every project below is open source and already does this job today. Fork one, self-host it, or take the parts you need - the build prompt further down assumes an empty file, and this is the shortcut past that. Licences differ; check the one on each card before you ship. All Schedule & Chill alternatives, with the arithmetic →

What a replacement has to do

  • Accept scheduling requests (via REST or MCP), store media, enqueue scheduled deliveries, and publish posts to connected LinkedIn accounts.

What it still won’t have

  • Hosted MCP server and prebuilt MCP adapters for multiple AI clients
  • The vendor's free hosted tier and any existing user data already in their service
  • Fast bug fixes and human support from the product author
  • The convenience of an already-approved platform adapter (other platforms in review)

What remains hard

  • Product polish and ongoing maintenance
Read the build prompt

First-year cost

No published price

Schedule & Chill does not publish a price we could read, so there is nothing to compare against. What building costs is below.

Money you would actually spend

Keep paying
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Subscription price × seats × 12

Build it
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AI build —APIs + hosting —

Time you would spend

—

—

What you would spend

What we assumed

The verdict above measures whether you could build it. This one is only about money.

Runnable build prompt

Not run yet
Build a self-hosted minimal Schedule & Chill clone using Node.js (Express) + PostgreSQL + Redis + Bull for background jobs, and an S3-compatible storage (MinIO or AWS S3). Core features in scope: REST API with bearer-token API keys (POST/GET/PUT/DELETE /api/posts, /api/media, /api/accounts), MCP-compatible HTTP server at /mcp implementing tools: schedule_post, list_accounts, upload_media, get_analytics (return JSON matching simple MCP tool patterns), OAuth linking for LinkedIn and secure token storage, resumable chunked media uploads to S3, a background scheduler worker to enqueue and deliver posts to LinkedIn and poll publish status, media tagging and search, and basic analytics endpoints (GET /api/analytics). Out of scope: native adapters for other platforms (TikTok, Instagram) and hosted multi-tenant billing. Require robust error handling, request validation, unit and integration tests for API and worker flows, Docker compose for local dev, and environment-variable driven config for secrets and S3. Include health checks and retry/backoff logic for delivery failures.
How we checked5 sources · 2/3 runs agreed · evidence score 60

How the score was reached

  • Partly verdict base52
  • An open-source build was found+5
  • 5 cited sources+3
  • Evidence score60

The base comes from the verdict. Everything under it is a check that either happened or did not, and each one is a fact frozen in this record rather than a judgement made at render time - so the same evidence always produces the same number.

How scoring works →

Cited sources · 5

Every page the run actually retrieved.

Integrity checks

What held up, and what did not.

! 2 of 3 runs agreed; the verdict is the majority✓ Citations limited to fetched pages! 1 moat recorded