mapbox-mcp-devkit-patterns

name mapbox-mcp-devkit-patterns description Integration patterns for Mapbox MCP DevKit Server in AI coding assistants. Covers setup, style management, token management, validation workflows, and documentation access through MCP. Use when building Mapbox applications with AI coding assistance. 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 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: Run validate_style_tool to check style JSON is spec-compliant Run validate_expression_tool to check all data expressions in paint/layout properties Run check_color_contrast_tool to verify text labels meet WCAG accessibility standards Run compare_styles_tool to diff the new style against current production style Token management — use these exact steps: Run create_token_tool to create scoped tokens for each environment (dev/staging/prod) Run list_tokens_tool to verify existing tokens and their scopes Reference Files Load these references as needed for detailed guidance: references/setup.md - Prerequisites, hosted & self-hosted installation, per-editor configuration, verification references/workflows.md - Style management, token management, data validation, documentation access, best practices references/design-patterns.md - 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 Model Context Protocol Mapbox Style Specification Mapbox API Documentation Token Scopes Reference 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