Buildable generates project plans for SaaS ideas and turns them into executable development tasks that stream directly to AI coding assistants through the Model Context Protocol. Instead of writing code like other AI tools, it decides what needs to be built, structures the repository, sets up testing frameworks, and creates a prioritized task list that any MCP-compatible AI can read and act on.
This system starts by analyzing a SaaS concept and generating a complete project plan broken into actionable development tasks. It then scaffolds the repository structure automatically, including CI/CD pipeline configuration. The technical approach centers on MCP integration, which lets developers connect their preferred AI assistant to the project plan by copying an API key and installing the MCP server in their code editor. The AI can then read the plan, understand the codebase context, and execute tasks according to the generated roadmap.
Repository scaffolding happens automatically with GitHub integration. Buildable creates private repositories and pushes the initial structure with build configurations already in place. The system handles multiple technology stacks including React, Rails, Go, and Rust without requiring framework-specific templates. This stack-agnostic approach means the scaffolding logic adapts to whatever technologies the project plan specifies.
Task management runs through a live Kanban board that updates automatically based on CI status. Cards move between columns as the build pipeline reports success or failure, giving real-time visibility into development progress. Buildable exports project data as JSON or pushes tasks directly to GitHub Issues for teams that prefer working in their existing workflow tools.
The CLI tool handles authentication and MCP wiring. Developers install it locally to establish the connection between Buildable's servers and their development environment. Row-Level-Security isolates project data at the database level, ensuring teams can't access each other's plans or repository configurations even when hosted on shared infrastructure.
MCP acts as the bridge between planning and execution. The protocol defines how AI assistants request project context, read task specifications, and report completion status back to Buildable's servers. Any AI that implements the MCP specification can connect, which currently includes several major models. The assistant receives structured task data including file paths, function signatures, and testing requirements rather than vague instructions.
GitHub integration goes beyond repository creation. Buildable monitors commit history and pull request status to update task cards automatically. When CI pipelines fail, the Kanban board reflects that state immediately. Teams can configure which GitHub events trigger updates to keep the planning view synchronized with actual development activity.
The Pro plan includes five project generations monthly for fifteen dollars. Team accounts cost twenty-nine dollars per user monthly and include twenty project generations. Both plans offer a seven-day free trial. The generation limit means teams need to plan which SaaS ideas warrant full project scaffolding versus manual planning.
Technical limitations center on generation quotas. Pro users hit the five-project cap quickly if experimenting with multiple concepts. Team plans provide more headroom but still cap at twenty generations regardless of team size. Buildable doesn't offer unlimited generation tiers, which constrains agencies or studios evaluating many client projects monthly. MCP compatibility requires AI assistants that implement the protocol specification, limiting which coding tools can integrate directly with task streams.
