polaris-mcp-server

Exposes Shopify's Polaris UI component library as structured, queryable resources through the Model Context Protocol (MCP), allowing AI assistants to introspect component APIs, props, and usage patterns without making external HTTP calls. The server implements MCP's resource protocol to serve component metadata as JSON schemas that describe each component's interface, making it possible for LLMs to reason about component compatibility and correct prop usage during code generation.

Provides structured type information for Polaris component props, enabling AI assistants to understand required vs optional props, prop types (string, boolean, enum, ReactNode), and default values. The server parses or exposes TypeScript type definitions from the Polaris library, allowing LLMs to generate code that respects prop constraints and avoid runtime errors from invalid prop combinations.

Surfaces curated or extracted code examples for Polaris components through MCP resources, allowing AI assistants to reference real, working usage patterns when generating code. The server likely indexes component examples from Polaris documentation or a curated example set, making them queryable by component name or use case, so LLMs can ground their output in proven patterns rather than generating novel code.

Tracks and exposes the version of the Polaris library being served, allowing AI assistants to understand which component APIs and features are available in the current context. The server maintains version metadata and can serve version-specific schemas, enabling LLMs to generate code compatible with the specific Polaris version in use rather than making assumptions based on training data.

Exposes relationships between Polaris components (e.g., which components can be nested, which components depend on context providers, which components work together idiomatically) as queryable metadata. The server likely analyzes component definitions to infer composition rules, allowing LLMs to understand valid component hierarchies and avoid generating invalid nesting or missing required parent components.

Implements the MCP server protocol to register Polaris-related tools and resources that AI assistants can discover and invoke. The server exposes capabilities through MCP's standard tool and resource endpoints, allowing compatible clients (like Claude Desktop) to understand what operations are available and how to call them with proper parameter schemas.