Vision Driven Design

MCP serverEverything else

Bi-directional traceability for AI-assisted development: 8-phase spec-driven chain, 7 gates.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use Vision Driven Design

Install Vision Driven Design

The server’s own address, for the clients that take one directly. Or connect ahel onceand every client you use reads it from one address, with the account kept on ahel rather than in each client’s config.

  • Claude Code

    claude mcp add --transport http vision-driven-design 'https://vdd.simonmak.com/api/sse'

    Run it once in your project, then open /mcp to approve any sign-in the server asks for.

  • Claude Desktop

    https://vdd.simonmak.com/api/sse

    Add a custom connector in Settings, paste this address, and approve the sign-in.

  • Cursor

    cursor://anysphere.cursor-deeplink/mcp/install?name=vision-driven-design&config=eyJ1cmwiOiJodHRwczovL3ZkZC5zaW1vbm1hay5jb20vYXBpL3NzZSJ9

    Open the link and Cursor adds the server at that address.

  • ChatGPT

    https://vdd.simonmak.com/api/sse

    In Settings, enable Developer mode, create an MCP app, and paste this address. Your plan and workspace must allow custom apps.

  • Codex

    codex mcp add vision-driven-design --url 'https://vdd.simonmak.com/api/sse'

    Run it once, then sign in with codex mcp login vision-driven-design if the server asks for an account.

From the project's README

As published by simonplmak-cloud/vision-driven-design in README.md.

From vision to verified impact — an AI-native, fully autonomous software development methodology.

Provide a human vision statement. The AI autonomously researches, audits your codebase, generates specs and plans, implements, and validates — with bi-directional verification at every junction to ensure nothing is missed or invented.


graph LR
    V[1. Vision<br/>Human Input] -->|<-->| S[2. Strategy<br/>AI Research]
    S -->|<-->| T[3. Tactics<br/>AI Audit]
    T -->|<-->| SP[4. Specs<br/>SDD]
    SP -->|<-->| PL[5. Plan]
    PL -->|<-->| TK[6. Tasks]
    TK -->|<-->| IM[7. Implement]
    IM -->|<-->| VS[8. Validate<br/>Impact Verified]

    style V fill:#4CAF50,color:#fff
    style S fill:#2196F3,color:#fff
    style T fill:#FF9800,color:#fff
    style SP fill:#9C27B0,color:#fff
    style VS fill:#4CAF50,color:#fff

Table of Contents

  • Quick Start
  • How It Works
  • Commands
  • Installation
  • MCP API
  • Domains Covered
  • Best-Practice Benchmark
  • Documentation
  • Repository Structure
  • Credits
  • License

Quick Start

# One-line install
curl -sSL https://raw.githubusercontent.com/simonplmak-cloud/vision-driven-design/main/scripts/install.sh | bash

Then in your project:

/vdd:init                          # Generate project constitution
/vdd:vision "your vision here"     # The only human input required

# Or run end-to-end in one command:
/vdd:e2e "your vision here"        # Full chain: init→vision→...→validate

The AI handles the rest — researching, auditing, generating specs, planning, implementing, and validating — with self-gating at 7 bi-directional verification junctions.

Tutorial → — 30-minute walkthrough building a real project.

# Want human gates? Add to constitution.md:
## VDD Mode: gated

How It Works

VDD follows Goldratt's recursive Strategy-Tactic decomposition: every phase is simultaneously the Tactic for its parent and the Strategy for its child.

PhaseS&T RoleOutput
0. Constitution(pre-chain)constitution.md — Immutable project rules
1. VisionL1 Strategy: What impact?vision.md — Impact model, success metrics
2. StrategyL1 Tactic → L2 Strategystrategy.md — Research, 12 pillars, risk register
3. TacticsL2 Tactic → L3 Strategytactics.md — Codebase audit, 38 action items
4. SpecsL3 Tactic → L4 Strategyspec.md — MoSCoW acceptance criteria
5. PlanL4 Tactic → L5 Strategyplan.md, data-model.md, contracts/
6. TasksL5 Tactic → L6 Strategytasks.md — Test-first atomic tasks
7. ImplementL6 Tactic → L7 StrategyCode — Per-task commits with full traceability
8. ValidateL7 Tactic — Did it work?impact-report.md — Drift + impact verification

7 bi-directional gates verify both directions at every junction (108 total checks). Each gate validates 4 S&T assumptions: Necessity, Achievability, Sufficiency, Warnings.

Every code commit traces back to the original vision statement:

V-001 → S-002 → T-003 → SP-004 → PL-005 → TK-006 → commit

Commands

CommandPhaseAction
/vdd:init0Generate constitution.md from project context
/vdd:vision "statement"1Expand freeform vision → structured vision.md
/vdd:strategize2Load domain primers, spawn research subagents, synthesize strategy.md
/vdd:tactics3Audit repo → gap analysis → tactics.md
/vdd:specify <ID | "desc">4Generate spec.md (or freeform — skips V/S/T)
/vdd:clarify <feature>4Clarification pass on a spec
/vdd:plan <feature>5Generate plan.md, data-model.md, contracts/
/vdd:tasks <feature>6Generate tasks.md
/vdd:get-next-task <feature>7Extract next uncompleted task
/vdd:implement <task-id>7Execute single task, verify, commit
/vdd:validate8Full-chain traceability + drift + impact report
/vdd:traceanyBidirectional traceability matrix
/vdd:analyze <feature>anyCross-artifact consistency analysis
/vdd:amend "what changed"anyCascade requirement change through full chain
/vdd:detect-environmentanyReport per-phase tool/MCP requirements + available capabilities
/vdd:e2e "vision statement"0–8End-to-end: run full 8-phase chain in one call, writes all 10+ template files
/vdd:e2e -clone <domain>7Clone: crawl site (browserless/fetch) into a full dataset + exact UI/UX + rebuilt backend + generated schema + AI tools + deployable dynamic site (vdd/clone-site/) from a domain (https/http/www/bare)

Installation

# OpenCode
git clone https://github.com/simonplmak-cloud/vision-driven-design.git \
  ~/.config/opencode/skills/vision-driven-design/

# Claude Code
git clone https://github.com/simonplmak-cloud/vision-driven-design.git \
  ~/.claude/skills/vision-driven-design/

# Cursor
git clone https://github.com/simonplmak-cloud/vision-driven-design.git \
  .cursor/skills/vision-driven-design/

Local MCP (from source)

To run the MCP server locally (stdio) instead of the public SSE endpoint:

# 1. Clone the repo
git clone https://github.com/simonplmak-cloud/vision-driven-design.git

# 2. Install deps + build the TypeScript packages
cd vision-driven-design
pnpm install
pnpm -r build

# 3. Point your agent at the built stdio entry point

OpenCode (opencode.json):

"vdd": {
  "type": "local",
  "command": ["node", "<repo>/packages/vdd-mcp/dist/stdio.js"],
  "enabled": true
}

Claude Desktop (claude_desktop_config.json):

"vdd": {
  "command": "node",
  "args": ["<repo>/packages/vdd-mcp/dist/stdio.js"],
  "type": "stdio"
}

MCP API

VDD is available as a public MCP server at https://vdd.simonmak.com/api/sse. 16 tools, SSE transport with JSON-RPC 2.0, no API key required.

Agent Configuration

OpenCode — add to opencode.json:

"vdd": {
  "type": "remote",
  "url": "https://vdd.simonmak.com/api/sse",
  "timeout": 120000
}

Claude Desktop — add to claude_desktop_config.json:

"vdd": {
  "command": "npx",
  "args": ["-y", "@simonmak-ascent/mcp"],
  "type": "stdio"
}

Cursor — add MCP server URL: https://vdd.simonmak.com/api/sse

Any SSE-compatible agent — endpoint: https://vdd.simonmak.com/api/sse

MCP Tools (16)

vdd_init, vdd_vision, vdd_strategize, vdd_tactics, vdd_specify, vdd_clarify, vdd_plan, vdd_tasks, vdd_get_next_task, vdd_implement, vdd_validate, vdd_trace, vdd_analyze, vdd_amend, vdd_clone, vdd_detect_environment.

The one-call e2e shortcut is not an MCP tool (it duplicates the phase sequence); use the CLI vdd e2e "vision" instead.

All tools accept: statement, projectRoot, actionItemId, feature, taskId, description, availableTools, capabilities, researchFindings, artifactFiles.

MCP Registry (Glama)

The server is listed on Glama, which builds it from source and publishes a hosted remote endpoint plus a Tool Definition Quality Score and maintenance rating:

Maintainer notes:

  • glama.json (repo root) is Glama's registry file. Its schema consumes exactly one field — maintainers. Build/transport/description metadata belongs in package.json and this README, not here; Glama ignores it.
  • Glama generates its own container build from the stdio entrypoint (packages/vdd-mcp/dist/stdio.js), wrapped with mcp-proxy. The root Dockerfile is for self-hosting the Streamable HTTP server, not for Glama.
  • After tool-definition changes: sync the repository and run Build & Release in the Glama admin. Tool-level scores refresh on the next sweep; the server-level coherence score re-runs less often.

API Reference

MethodDescription
GET /api/sseSSE stream (MCP client) or HTML docs (browser)
POST /api/sseJSON-RPC — initialize, tools/list, tools/call
# JSON-RPC call example
curl -X POST https://vdd.simonmak.com/api/sse \
  -H "Content-Type: application/json" \
  -d '{"jsonrpc":"2.0","method":"tools/call","params":{"name":"vdd_validate","arguments":{"projectRoot":"."}},"id":1}'

The full TypeScript engine (packages/vdd-engine, packages/vdd-mcp, packages/vdd-cli) is included in this repo.


Domains Covered

VDD loads domain-specific research patterns during the Strategy phase based on your vision:

DomainWhat it covers
WebAppUX, accessibility (WCAG 2.2), performance budgets, framework evaluation
Data StorageSchema design, indexing strategy, data governance, ACID vs eventual
ETLPipeline architecture, data quality, batch vs streaming
InfrastructureCI/CD, observability, security, scaling, disaster recovery
Human FactorsBehavioral economics, cognitive load, habit formation, accessibility cognition
Verification ToolchainPlaywright, Browserless, Sentry, CI/CD quality pipeline
Safety-CriticalFMEA/FTA, DO-178C/IEC 62304 safety integrity levels

human-factors.md and verification-toolchain.md are loaded unconditionally for every project.


Best-Practice Benchmark

VDD is benchmarked against NASA SE, CMMI REQM, DO-178C, IEC 62304, DORA, ISO 29148, and GitHub Spec Kit:

47/47 criteria matched (100%), 11 exceeded, 0 gaps.

Full benchmark matrix → | Compliance evidence templates →


Documentation

FileContents
SKILL.mdFull command reference and workflow
vdd/docs/tutorial.md30-minute walkthrough
vdd/docs/comparison.mdVDD vs SDD vs vibe coding vs TDD
vdd/docs/best-practice-benchmark.mdStandards alignment matrix
references/workflow-phases.mdStep-by-step phase instructions (authoritative)
references/artifact-templates.mdCopy-paste templates for all 11 artifacts
references/quality-gates.md7 gates with 108 checks + CI/CD
references/anti-patterns.md24 failure modes and fixes
references/compliance-evidence.mdDO-178C/IEC 62304/CMMI/ISO 29148 evidence maps
references/clone-workflow.mdWebsite cloning — crawl → dataset → deployable dynamic site
references/quick-reference.mdOne-page cheat sheet

Repository Structure

├── SKILL.md                         # Entry point — loaded by OpenCode
├── README.md                        # This file
├── AGENTS.md                        # Instructions for AI agents
├── constitution.md                  # Project constitution (dogfooded)
├── CHANGELOG.md                     # Versioned change history
├── CONTRIBUTING.md                  # Contribution guidelines
├── LICENSE.md                       # MIT
├── index.html                       # GitHub Pages landing page
├── pnpm-workspace.yaml              # Workspace config
├── package.json                     # Root package (Vercel + workspace)
├── vercel.json                      # Vercel deployment config
├── Dockerfile                       # Self-host build — Streamable HTTP MCP server
├── glama.json                       # Glama registry file (maintainers only)
├── domain-primers/                  # 7 domain research patterns
│   ├── webapp.md
│   ├── data-storage.md
│   ├── etl.md
│   ├── infrastructure.md
│   ├── human-factors.md             # Loaded unconditionally
│   ├── verification-toolchain.md    # Loaded unconditionally
│   └── safety-critical.md           # FMEA/FTA, DO-178C/IEC 62304
├── references/                      # 10 authoritative reference docs
│   ├── INDEX.md                     # Navigation map
│   ├── quick-reference.md           # 1-page cheat sheet
│   ├── workflow-phases.md           # Phase order (authoritative)
│   ├── artifact-templates.md        # 11 artifact templates (authoritative)
│   ├── prompt-patterns.md           # AI prompts (authoritative)
│   ├── quality-gates.md             # 7 gates + 108 checks (authoritative)
│   ├── ai-agent-patterns.md         # Agent orchestration (authoritative)
│   ├── anti-patterns.md             # 24 failure modes (authoritative)
│   ├── traceability-matrix.md       # RTM format + CI/CD
│   └── compliance-evidence.md       # Evidence maps
├── vdd/                             # VDD chain artifacts
│   ├── vision.md                    # Vision, impact model, 17 impacts
│   ├── strategy.md                  # 12 strategic pillars
│   ├── tactics.md                   # 38 action items (all DONE)
│   ├── impact-report.md             # Full-chain traceability + drift
│   ├── docs/                        # 16 guides and references
│   └── specs/                       # 3 feature specs
├── packages/                        # TypeScript monorepo
│   ├── vdd-engine/                  # Shared core — 17 phase functions + meta.ts
│   ├── vdd-mcp/                     # MCP server — 16 tools, stdio + Streamable HTTP
│   └── vdd-cli/                     # CLI binary — 17 subcommands
├── api/                             # Vercel MCP endpoint
│   └── sse.js                       # MCP SSE + JSON-RPC 2.0 handler
├── scripts/                         # 4 installer/helper scripts
└── .github/                         # GitHub config
    ├── CODEOWNERS
    ├── ISSUE_TEMPLATE/
    └── workflows/

Credits

Built on:

  • Goldratt's Strategy-and-Tactic Tree — recursive decomposition at every phase
  • Impact Mapping (Gojko Adzic) — goal → actors → impacts → deliverables
  • GitHub Spec Kit — spec-driven development with AI agents
  • NASA Systems Engineering — bidirectional traceability and verification chains
  • CMMI Requirements Management — bidirectional traceability of requirements

License

MIT — see LICENSE.md

Advanced
Delivery
vision-driven-design MCP server → your ahel gateway (mcp.ahel.ai) → every connected AI client.
Catalog kind
mcp-server
Gateway key
io-github-simonplmak-cloud-vision-driven-design
Source
github.com/simonplmak-cloud/vision-driven-design
Hosted endpoint
https://vdd.simonmak.com/api/sse