PromptOT

PromptOT is a prompt management platform designed to help teams organize, version, evaluate, and deliver prompts for large language models (LLMs) in production environments. It addresses the common challenges of prompt sprawl—where prompts are scattered across documents, chat threads, and codebases—by providing a centralized system that treats prompts as production code, complete with version control, evaluation workflows, and deployment options. The platform is suited for a range of users, from solo developers and startups to large-scale teams and agencies managing multiple clients or projects.

Prompts in PromptOT are authored using six typed, validated block types: role, context, instructions, guardrails, output_format, and custom. These blocks can be composed, reused, and independently versioned. The system supports variable interpolation and compile-time schema validation to ensure prompts are consistent and reliable. Semantic versioning is built in, allowing users to track every change with full history, commit messages, diffs, and one-click rollback or publishing through review workflows. Environment-scoped keys make it possible to differentiate between production, staging, and draft versions, ensuring that the right prompt version is delivered to the right context.

Evaluation features let users run any prompt version against saved test cases across multiple LLMs used in production. The platform provides tools to compare pass/fail results, latency, and token cost, as well as rule-based criteria such as string containment, regex, and similarity matching. API delivery is available through a REST endpoint, with HMAC-signed webhooks for change notifications. PromptOT also functions as an MCP (Model Control Protocol) server, enabling direct integration with tools like Claude Desktop, Cursor, Codex CLI, Windsurf, Zed, and ChatGPT, without requiring additional SDKs or code changes. Environment-aware delivery ensures that development clients can access drafts while production clients receive published versions, all secured by signed requests.

An AI co-pilot feature is included, allowing users to get suggestions for prompt improvement, explanations for underperformance, or draft new iterations, with tracked diffs and per-prompt model routing for cost control. Pricing is simple, with a free tier offering up to three projects, five prompts per project, 1,000 API calls per month, 50 AI credits per month, and support for up to five team members. Every plan includes access to the full editor, all block types, unlimited versions, and both API and MCP delivery options.