metastory AI is an AI-powered product management platform that helps product managers, agencies, and software houses convert early-stage ideas into structured development requirements. It targets the pre-development phase, generating Product Requirements Documents, user stories, and acceptance criteria from natural-language conversations so that engineering teams receive unambiguous, actionable specifications.
Key Features
- AI PRD Generation: Start a conversation describing your project context and metastory AI generates a comprehensive Product Requirements Document organized into modules, features, and sub-features within seconds.
- User Stories and Acceptance Criteria: The platform automatically produces atomic user stories with detailed acceptance criteria written in Gherkin format, reducing ambiguity and giving developers clear conditions to build and test against.
- Jira Two-Way Sync: Push generated epics and stories directly to Jira. A live connection keeps the high-level product vision in metastory synchronized with day-to-day development tracking in Jira, so both tools stay consistent without manual updates.
- Figma Integration: Import Figma screens and link them directly to specific requirements. Figma Screen Update Tracking keeps documentation aligned as designs change over time.
- AI Estimation Board: Receive instant effort and cost predictions across frontend, backend, and QA tasks based on feature complexity, helping teams scope work before committing to timelines.
- AI Reverse Engineering: Upload a screenshot of an existing UI to automatically extract a full feature list and requirements, useful for auditing or documenting legacy products.
- Reusable Feature Libraries: Save common feature sets such as authentication flows or payment integrations and reuse them across multiple client projects to reduce repetitive documentation work.
Meta Coding and MCP Integration
metastory AI includes a Model Context Protocol (MCP) Server that serves structured PRD context directly to AI coding assistants including Cursor, Claude Code, and GitHub Copilot. The Meta Coding workflow ensures AI-generated code stays aligned with documented product requirements, reducing logical errors and hallucinations that occur when coding tools operate without structured context. This is particularly useful for teams practicing AI-assisted development workflows that need a reliable source of product truth.
Use Cases
- Product managers who need developer-ready requirements generated from early-stage product conversations, without spending hours on manual documentation.
- Agencies managing multiple client projects who benefit from reusable feature libraries and consistent documentation standards across engagements.
- Software houses running AI-assisted development pipelines that need structured PRD context feeding their coding tools through MCP.
Pricing
- Free: Core requirement gathering and AI generation features with no credit card required.
- Pro (approximately $10 per month): Advanced AI capabilities, deeper project insights, and full Jira and Figma integration suites.
- Business and Agency: Custom plans for multi-user teams with reusable libraries, RAG-grounded AI assistance, and dedicated support.
