Mowgli MCP — Integration Guide¶
What it does: Mowgli is an intelligent product canvas that connects to coding agents via MCP. It lets product teams and developers iterate on product design — from sweeping new flows down to surgical component tweaks — and sync changes back to code, all through natural language conversations.
Why it matters: The design→development handoff is one of the highest-friction points in product development. Mowgli MCP eliminates "design drift" by making the product canvas directly accessible to AI coding agents, enabling faithful design-to-code translation and real-time design iteration without Figma exports, screenshots, or manual specification.
Quick Info¶
| Field | Value |
|---|---|
| Transport | Streamable HTTP (remote) |
| Authentication | API key / OAuth |
| Endpoint | https://app.mowgli.ai/mcp |
| Source | app.mowgli.ai |
| Category | Product Design & UX |
| CorpusIQ Verdict | ★★★★☆ — Game-changing for product teams, early-stage |
Setup¶
Prerequisites¶
- Mowgli account (free tier available)
- Mowgli project with an active canvas
- API key from Mowgli dashboard → Settings → API
1. Get API Key¶
# In Mowgli dashboard:
# Settings → API → Generate Key
# Copy the key — it's shown once
2. Configure MCP Client¶
Add to your claude_desktop_config.json or equivalent:
{
"mcpServers": {
"mowgli": {
"type": "sse",
"url": "https://app.mowgli.ai/mcp",
"headers": {
"Authorization": "Bearer <your-api-key>"
}
}
}
}
For Claude Code or terminal-based clients:
{
"mcpServers": {
"mowgli": {
"command": "npx",
"args": ["-y", "@mowgli/mcp-server"],
"env": {
"MOWGLI_API_KEY": "<your-api-key>",
"MOWGLI_PROJECT_ID": "<your-project-id>"
}
}
}
}
Available Tools¶
| Tool | Description |
|---|---|
get_canvas |
Retrieve the current product canvas — screens, flows, components |
get_screen |
Get a specific screen's design, components, and states |
get_component |
Get detailed specs for a specific component (colors, spacing, variants) |
update_component |
Modify a component's properties (text, color, layout, state) |
create_screen |
Create a new screen with specified components and layout |
add_component |
Add a new component to an existing screen |
get_design_tokens |
Retrieve the project's design tokens (colors, typography, spacing) |
suggest_improvements |
AI-powered suggestions for UX improvements on a screen |
export_for_code |
Export screen/component as structured data for code generation |
sync_from_code |
Update canvas to reflect code changes (keep design in sync) |
Operator Workflows¶
Design Review → Code¶
Agent: "Review the onboarding flow in canvas and suggest improvements."
→ get_canvas(flow: "onboarding")
→ suggest_improvements(screen: "onboarding-step-2")
Agent: "Apply the suggestion to add a progress indicator and update the CTA text."
→ update_component(screen: "onboarding-step-2", component: "cta-button", text: "Continue to Step 3")
→ add_component(screen: "onboarding-step-2", type: "progress-bar", position: "top")
Agent: "Now generate the React code for this updated screen."
→ export_for_code(screen: "onboarding-step-2", framework: "react")
Rapid Prototyping¶
Agent: "Create a settings page with profile, notifications, and billing sections."
→ create_screen(name: "Settings", sections: ["profile", "notifications", "billing"])
Agent: "Add email notification toggles: marketing, product updates, security alerts."
→ add_component(screen: "Settings", section: "notifications", type: "toggle-group", items: ["marketing", "product-updates", "security-alerts"])
Agent: "Use the project's design tokens for consistent styling."
→ get_design_tokens()
→ [Applies tokens to new components]
Design Drift Detection¶
Agent: "Compare the current checkout screen in code against the Mowgli canvas."
→ get_canvas(flow: "checkout")
→ [Agent compares against codebase]
Agent: "Found 3 discrepancies: button color, spacing in form, missing loading state. Update code to match canvas."
→ export_for_code(screen: "checkout", format: "diff")
Limitations¶
- Early-stage product: Mowgli is newer than established tools like Figma
- Canvas complexity: Very large canvases (50+ screens) may hit token limits
- No Figma import: Cannot yet import existing Figma files (on roadmap)
- Component library: Growing but smaller than Figma community libraries
- Real-time collaboration: Single-user editing via MCP; multi-user coming
Alternatives¶
| Server | Best For |
|---|---|
| Figma MCP | Established design teams with existing Figma files |
| Design Context Bridge | Direct Figma-to-code (reads Figma files without Mowgli canvas) |
| Penpot MCP | Open-source design tool alternative |
| Builder.io MCP | Visual CMS + design-to-code for marketing sites |
CorpusIQ Assessment¶
Strategic Value: High. The product canvas approach — where design lives as structured data that both humans and AI can manipulate — is the future of design-to-code workflows. Mowgli's MCP integration makes this vision tangible today.
Integration Difficulty: Low. Remote endpoint with API key auth. No local dependencies.
Risk: Medium. Early-stage product means potential API changes and growing pains. The core concept is sound.
Recommendation: Catalog and recommend for product teams who want AI-assisted design iteration. Pairs exceptionally well with coding agents (Claude Code, Cursor, Codex) for design-to-code workflows. Watch for Figma import support (on roadmap) which would dramatically expand utility.