Hoofy FAQs

Question 1

What is Hoofy's approach to managing project knowledge?

Accepted Answer

Hoofy utilizes a Knowledge Graph to connect project observations with typed, directional relations (e.g., depends_on, caused_by), building a navigable web of knowledge. This, combined with persistent SQLite memory, ensures AI agents remember past decisions, bugs, and patterns across sessions.

Question 2

What is Hoofy and what problem does it solve?

Accepted Answer

Hoofy is an MCP server designed to empower AI development by providing persistent memory, structured specifications, and adaptive change management. It solves the problem of AI hallucination and inconsistency by ensuring projects are built exactly as intended through a Spec-Driven Development approach.

Question 3

How does Hoofy ensure accuracy in AI-driven software development?

Accepted Answer

Hoofy ensures accuracy through features like a mandatory Context Check stage that detects conflicts and ambiguities before development, business rules extraction from requirements using BRG taxonomy, and adaptive change pipelines that prevent issues and enforce clarity.

Question 4

How does Hoofy facilitate efficient task execution for AI teams?

Accepted Answer

Hoofy's Wave Assignments feature groups tasks into parallel execution waves derived from dependency graphs. This clearly indicates which tasks can run concurrently and which must wait, optimizing team coordination and identifying the critical path for faster project delivery.

Question 5

Is Hoofy compatible with my existing AI development tools?

Accepted Answer

Yes, Hoofy functions as an MCP (Model Context Protocol) server. This means it is compatible with any MCP-enabled AI tool, including Claude Code, Cursor, VS Code Copilot, OpenCode, and Gemini CLI, allowing seamless integration into your workflow.

Hoofy

Hoofy

Key Features

Use Cases

Key Features

Use Cases