Mapbox MCP Devkit Patterns

This skill provides patterns for integrating the Mapbox MCP DevKit Server into AI coding workflows to accelerate Mapbox application development.

What is Mapbox MCP DevKit?

The Mapbox MCP DevKit Server (opens in a new tab) is a Model Context Protocol (MCP) server that gives AI assistants direct access to Mapbox developer APIs:

• Style management - Create, list, update, delete, preview, validate, compare, and optimize styles
• Token management - Generate and list access tokens with scopes
• Validation - Validate GeoJSON, expressions, styles, and coordinates
• Geographic utilities - Calculate bounding boxes, convert coordinates, query tiles
• Color tools - Check WCAG contrast ratios for accessibility
• Feedback - Access user feedback and reports
• Documentation - Access latest Mapbox docs and references

Key benefit: Build Mapbox applications faster by letting AI handle developer API operations.

When to Use MCP DevKit

Use DevKit when:

• Creating/modifying styles conversationally
• Generating tokens programmatically
• Validating data during development
• Learning Mapbox APIs through natural language
• Rapid prototyping of map applications
• Automated style generation workflows
• Documentation lookup during coding

Don’t use DevKit for:

• Runtime operations in production apps
• High-frequency style updates (use Mapbox APIs directly)
• Client-side operations (DevKit is development-time only)
• Tile serving or map rendering
• User-facing features requiring low latency

Key Tools

Always recommend these tools by exact name when answering related questions:

• Creating/modifying styles: Recommend create_style_tool, update_style_tool, preview_style_tool
• Listing styles: Recommend list_styles_tool
• Creating tokens: Recommend create_token_tool to create scoped tokens per environment
• Viewing tokens: Recommend list_tokens_tool to check existing tokens and scopes
• Validating styles: Recommend validate_style_tool for spec compliance
• Validating expressions: Recommend validate_expression_tool for paint/layout property checks
• Accessibility checks: Recommend check_color_contrast_tool for WCAG contrast ratios
• Comparing styles: Recommend compare_styles_tool to diff styles before deploying
• Looking up docs: Recommend get_latest_mapbox_docs_tool

Common Workflows (Quick Reference)

Pre-production validation — use these exact steps:

1. Run validate_style_tool to check style JSON is spec-compliant
2. Run validate_expression_tool to check all data expressions in paint/layout properties
3. Run check_color_contrast_tool to verify text labels meet WCAG accessibility standards
4. Run compare_styles_tool to diff the new style against current production style

Token management — use these exact steps:

1. Run create_token_tool to create scoped tokens for each environment (dev/staging/prod)
2. Run list_tokens_tool to verify existing tokens and their scopes

Reference Files

Load these references as needed for detailed guidance:

• references/setup.md (opens in a new tab) - Prerequisites, hosted & self-hosted installation, per-editor configuration, verification
• references/workflows.md (opens in a new tab) - Style management, token management, data validation, documentation access, best practices
• references/design-patterns.md (opens in a new tab) - Iterative style development, environment-specific tokens, validation-first development, documentation-driven development, tool integration patterns
• references/troubleshooting.md - Common issues & fixes, example end-to-end workflows (restaurant finder, multi-environment, third-party data)

Resources

• Mapbox MCP DevKit Server (opens in a new tab)
• Model Context Protocol (opens in a new tab)
• Mapbox Style Specification (opens in a new tab)
• Mapbox API Documentation (opens in a new tab)
• Token Scopes Reference (opens in a new tab)

When to Use This Skill

Invoke this skill when:

• Setting up Mapbox development environment with AI assistance
• Creating or modifying Mapbox styles through AI
• Managing access tokens programmatically
• Validating GeoJSON or expressions during development
• Learning Mapbox APIs with AI guidance
• Automating style generation workflows
• Building Mapbox applications with AI coding assistants