AI-powered Model Context Protocol server that slashed search time by 52%, accelerated onboarding by 78%, and delivered $2.3M in annual savings while transforming how thousands of developers interact with our design system.
An enterprise design system serving thousands of developers needed a better way to deliver guidance at the point of use. This is the story of how we identified the problem, built an AI-powered solution, and achieved measurable business impact across engineering, design, and product teams.
Please note: Details are generalized to protect intellectual property while demonstrating problem-solving approach and strategic outcomes.
Our design system served thousands of professionals building experiences for hundreds of thousands of customers. Despite comprehensive documentation, developers faced significant friction:
Transform fragmented developer tools into an intelligent orchestration system that provides real-time, context-aware guidance grounded in design system knowledge. The goal: catch issues before commit, accelerate onboarding, and shift quality left in the development cycle.
Single layer coordinating all tools
Instead of teams juggling multiple disconnected tools, create one intelligent orchestration layer that coordinates ESLint, TypeScript, axe-core, & more providing a unified feedback experience.
Context-aware validation
Go beyond generic syntax checking. Validate against actual design system standards, component patterns, & organizational conventions providing guidance that understands your codebase.
Issues caught in IDE, not review
Shift quality left by catching issues during development, not in code review. Provide instant, actionable feedback while developers code before they even commit.
System improves from team patterns
Learn from team interactions, common questions, & emerging patterns. The system gets smarter over time, adapting to your organization's evolving needs & standards.
We implemented an AI-powered Model Context Protocol server integrated with design system knowledge to assist developers in real time, with complementary design governance and QA automation
The foundation of accurate AI responses starts with comprehensive data collection. We aggregate design system knowledge from multiple sources to build a complete picture of how the design system is documented, implemented, & used in practice.
The MCP Server coordinates validation tools and provides intelligent interpretation
search_dsvalidategeneratecheck_a11yanalyticsThe server validates against design system standards, not just syntax. It understands component patterns, design tokens, accessibility requirements, and codebase conventions. Every validation is grounded by executing actual analysis tools and reporting real results:
AI orchestrates, tools execute. When a developer asks a question, the AI determines which tools to run, executes them via their APIs, and interprets the actual results. The AI adds contextual explanations and suggests fixes, but only reports issues that real tools found. Zero hallucinations, 100% accuracy.
The true power comes from meeting developers where they work. Through a VS Code extension, GitHub Actions, & an analytics dashboard, the system delivers contextually accurate, actionable guidance directly in existing workflows.
Real-time guidance while coding
PR validation & compliance
Usage & adoption metrics
Developers get instant, accurate answers about components, patterns, and best practices without leaving their workflow or waiting for design team support.
The MCP server integrates directly into VS Code, Github Actions, and a CLI, providing real-time design system guidance and validation where it's most useful. Developers get instant answers, component recommendations, and automated validation—eliminating context switching and documentation hunting.
search_ds to find the best match.validate for quick fixes.// In VS Code command palette
mcp.search_components({
query: 'primary button with loading'
}) // → returns component + props + usage
// Apply and validate
mcp.validate({
file: 'Button.tsx'
}) // → OK (a11y + tokens)// Triggers suggestion while typing
const button = <button type="Primary"...
// Tab autocompletes// Design System Validation
✓ Accessibility Check (WCAG 2.1 AA)
✓ Token Usage: 94% compliantTypical developer workflow without AI assistance
Streamlined developer workflow with AI assistance
By automating routine support and validation, the MCP server freed designers from repetitive questions and PR reviews. Design teams reclaimed 60% of their time, shifting from reactive support to strategic design work, innovation, and user research.
// Spec Snapshot
Component: PrimaryButton
Props: variant, size, isLoading
Tokens: color.primary.500, spacing.md, radius.sm
A11y: contrast ≥ 4.5:1, focus ring visible// Figma Checks
Component: PrimaryButton
Status: ✓ Implemented
Usage: 247 instances// Design System Validation
✓ Accessibility Check (WCAG 2.1 AA)
✓ Token Usage: 94% compliantDesigners acting as human documentation
AI handles routine questions automatically
Automated validation catches design system violations and accessibility issues before QA testing begins. Testing cycles dropped from 2-3 days to 4-6 hours, with WCAG compliance jumping from 67% to 94%.
{
"component": "PrimaryButton",
"checks": { "tokens": "pass", "contrast": "pass", "aria": "warn" },
"warnings": ["Add aria-live='polite' for dynamic label"]
}// Design System Validation
✓ Accessibility Check (WCAG 2.1 AA)
✓ Token Usage: 94% compliantTime-consuming manual verification
AI catches issues before QA testing
Real-time dashboards provide product owners with visibility into design system adoption, quality metrics, and delivery velocity. Predictable timelines replaced guesswork—features deliver 44% faster with 94% compliance. Data-driven insights enable better planning and resource allocation.
{
"feature": "Payments v2",
"compliance": 0.98,
"a11y": { "blocking": 0, "warnings": 2 },
"predicted_cycle_time_change": -0.18
}$ dsValidate
Scanned 1,247 files
Compliance: 94%
Blocked: 3Hidden complexity and rework
Consistent timelines with quality built-in
Six months post-launch, the AI-powered MCP server delivered transformative results across developer productivity, team efficiency, & business value.
As we continue to refine our MCP server, we're already seeing positive outcomes. The AI-powered design system is not just a tool; it's a partner that helps us deliver faster, more consistent, & higher-quality work.
Proofs of Concept: Rapid, low-risk PoCs validated technical feasibility, clarified scope, and built confidence before committing to full implementation.
Orchestrating Part‑Time Contributors: Planned around non-dedicated bandwidth with clear owners, weekly checkpoints, and tightly scoped workstreams to maintain momentum without burnout.
Stakeholder Alignment: Mapped decision-makers and influencers, ran demos tailored to their priorities, and maintained a shared roadmap and success metrics to keep everyone moving in the same direction.
Executive Buy‑In: Framed outcomes in business terms (time-to-value, risk reduction, scale), paired with live prototypes and pilot results to secure sponsorship and unblock resourcing.
This MCP server transformed our design system from a static documentation repository into an active development partner. By reducing friction, improving consistency, and accelerating delivery, we fundamentally changed how the design system serves the organization.
Want to dive deeper? Explore the detailed impacts and technical implementation