Pre-flight engineering vs post-flight observability — different stages of the same problem.
PromptLayer is an observability platform: log every prompt + response, version-control prompts, A/B test, analyze cost trends. It runs at the post-call layer. Promptibus MCP runs at the pre-call layer: pick the cheapest model that fits, rewrite to model-specific syntax, lint for broken flags, project the bill BEFORE you pay. The two stack naturally — Promptibus optimizes, PromptLayer logs what happened.
Use PromptLayer to track what your team's prompts cost over time. Use Promptibus to make each individual prompt cheaper + correct before it runs. Use both for the full picture.
| Feature | Promptibus | PromptLayer |
|---|---|---|
| Stage in workflow | Pre-call (engineering) | Post-call (observability) |
| Core value prop | Pick + optimize + lint cheaper prompts | Log + analyze + version prompts |
| Model coverage | 80+ models across 5 domains | All models via LLM SDK wrappers |
| Cost data | Projection BEFORE you pay (`get_pricing`) | Analytics AFTER you paid |
| Agent integration | Native MCP for Claude/Cursor/Continue/etc. | Python/TS SDK in your backend code |
| Team / versioning | No — single-user usage tracking only | Yes — prompt versioning + team workspaces |
| Free tier | 100 calls/day | Free dev tier; production needs paid plan |
Most teams should use BOTH. Promptibus before the call (lower cost, fewer retries), PromptLayer after (track what worked). They operate on different stages so there's no overlap.
Free tier: 100 calls/day. No credit card.