Hoofy

What Is Hoofy? — AI Development Companion for MCP

Hoofy solves three recurring AI-dev problems:memory loss between sessions,hallucinated implementations, andunstructured workflows. It's a single](https://github.com/HendryAvila/Hoofy/blob/main/docs/research-foundations.md)MCP (Model Context Protocol)server written in Go — one binary, zero external runtime dependencies.

Decision: "Switched to JWT" →(caused_by)→ Discovery: "Session storage doesn't scale" ↑(implements) ↑(relates_to) Bugfix: "Fixed token expiry" Pattern: "Retry with backoff"

AI coding assistants are powerful but forgetful and overconfident. Studies show experienced developers are19% slower with unstructured AI(METR 2025), and AI adoption without structure causes7.2% delivery instability(DORA 2025). Hoofy fixes this by making your AI remember context, follow specifications, and validate understanding before coding.

flowchart TB explore["sdd_explore\n(goals, constraints, unknowns)"] subgraph project ["New Project (greenfield)"] direction LR P1[Init] --> P1b[Principles] --> P2[Charter] --> P3[Requirements] --> P3b["Business\nRules"] P3b --> P4{Clarity Gate} P4 -->|Ambiguous| P3 P4 -->|Clear| P5[Design] --> P6[Tasks] --> P7[Validate] end subgraph bootstrap ["Existing Project (no specs)"] direction LR B1["sdd_reverse_engineer\n(scan codebase)"] --> B2["AI analyzes\nreport"] --> B3["sdd_bootstrap\n(write artifacts)"] end subgraph change ["Existing Project (changes)"] direction LR C1["sdd_change\n(type × size)"] --> C1b["Context\nCheck"] C1b --> C2["Opening Stage\n(describe/charter/scope)"] C2 --> C3["Spec + Design\n(if needed)"] C3 --> C4[Tasks] --> C5[Verify] end subgraph memory ["Memory (always active)"] direction LR M1["mem_session(action=start)"] --> M2["Work + mem_save"] M2 --> M3["Connect with Relations"] M3 --> M4["mem_session(action=end, summary)"] end explore -.->|"captures context before"| project explore -.->|"captures context before"| change bootstrap -.->|"enables"| change style explore fill:#8b5cf6,stroke:#7c3aed,color:#fff style P4 fill:#f59e0b,stroke:#d97706,color:#000 style P1b fill:#e879f9,stroke:#c026d3,color:#000 style P3b fill:#e879f9,stroke:#c026d3,color:#000 style C1b fill:#e879f9,stroke:#c026d3,color:#000 style B1 fill:#06b6d4,stroke:#0891b2,color:#fff style B3 fill:#06b6d4,stroke:#0891b2,color:#fff style P7 fill:#10b981,stroke:#059669,color:#fff style C5 fill:#10b981,stroke:#059669,color:#fff

Full workflow guide with step-by-step examples·Complete tool reference

curl -sSL https://raw.githubusercontent.com/HendryAvila/Hoofy/main/install.sh | bash

irm https://raw.githubusercontent.com/HendryAvila/Hoofy/main/install.ps1 | iex

# Go install (requires Go 1.25+) go install github.com/HendryAvila/Hoofy/cmd/hoofy@latest # Or build from source git clone https://github.com/HendryAvila/Hoofy.git cd Hoofy make build

claude mcp add --scope user hoofy hoofy serve

/plugin marketplace add HendryAvila/hoofy-plugins /plugin install hoofy@hoofy-plugins

{ "mcpServers": { "hoofy": { "command": "hoofy", "args": ["serve"] } } }

{ "servers": { "hoofy": { "type": "stdio", "command": "hoofy", "args": ["serve"] } } }

Add to~/.config/opencode/opencode.jsoninside the"mcp"key:

{ "mcp": { "hoofy": { "type": "local", "command": ["hoofy", "serve"], "enabled": true } } }

{ "mcpServers": { "hoofy": { "command": "hoofy", "args": ["serve"] } } }

Just talk to your AI. Hoofy's built-in instructions tell the AI when and how to use each system.

Auto-checks on startup, updates when you say so.

Hoofy already includes built-in server instructions, but a short policy block in your agent instructions file reinforces the workflow.

Note:sdd_init_projectauto-generates this in agent files. Add manually only if you run Hoofy in MCP-only mode.

Put this in your tool-specific instruction file:

- Claude Code:CLAUDE.md
- Cursor:.cursor/rules/hoofy.md
- OpenCode:AGENTS.md
- VS Code Copilot:.github/copilot-instructions.md
- Gemini CLI:GEMINI.md

## Hoofy — Spec-Driven Development Before coding any non-trivial change, use Hoofy specs first. - New projects: \sdd_init_project\ -> full pipeline - Existing projects without specs: \sdd_reverse_engineer\ -> \sdd_bootstrap\ - Ongoing work: \sdd_change\ (size/type adaptive) - Ad-hoc sessions: \sdd_suggest_context\ - Reviews: \sdd_review\ - Spec/code drift checks: \sdd_audit\ - Memory: \mem_save\, \mem_session\`

- New project?→sdd_init_projectand walk through the full 9-stage pipeline
- New feature?→sdd_change(type: "feature", size: "medium")at minimum
- Bug fix?→ Evensdd_change(type: "fix", size: "small")gives you context-check → describe → tasks → verify

Before jumping into a pipeline, usesdd_exploreto capture context from your discussion — goals, constraints, tech preferences, unknowns, decisions. It saves structured context to memory so the pipeline starts with clarity, not guesswork. Call it multiple times as your thinking evolves — it upserts, never duplicates.

Working on a project that never went through SDD? Don't skip specs — bootstrap them. Runsdd_reverse_engineerto scan the codebase, thensdd_bootstrapto generate the missing artifacts. This takes under a minute and means the change pipeline works with full context instead of flying blind. Medium/large changes are blocked without specs — and that's intentional.

- Start sessions by greeting the AI— it triggersmem_contextto load recent history
- Mention past decisions— "remember when we chose SQLite?" triggersmem_search
- Confirm session summaries— the AI writes them at session end, review them for accuracy

Hoofy's knowledge graph lets you connect related observations with typed, directional edges — turning flat memories into a navigable web. The AI creates relations automatically when it recognizes connections. You can also ask it to relate observations manually. Usemem_get(id=..., depth=...)`to explore the full graph around any observation.