React Analyzer MCP Server

The react‑analyzer‑mcp server bridges the gap between raw React source code and AI assistants by providing a Model Context Protocol (MCP) interface that can parse, analyze, and document React components on demand. Instead of manually inspecting dozens of JSX/TSX files, developers can ask an AI assistant to generate a comprehensive component inventory or detailed prop tables. This capability is especially valuable for teams that rely on AI‑driven code reviews, onboarding documentation, or automated QA tooling.

At its core, the server exposes three intuitive tools. The analyze-react tool ingests a single component’s source string and returns a structured summary of the component name, its exported API, and an exhaustive list of props with types, optionality, and default values. The analyze-project tool recursively scans a specified directory, applies the same analysis to every component found, and produces a ready‑to‑use Markdown documentation file. Finally, list-projects simply enumerates all subfolders under the configured root, enabling quick navigation across multiple component libraries or micro‑frontend projects. By delivering this information in JSON or Markdown, the MCP allows downstream AI agents to format responses exactly as required by a given workflow.

The value for developers lies in the elimination of manual documentation overhead. Teams can integrate this MCP into CI/CD pipelines to auto‑generate changelogs whenever a component’s API changes, or feed the output into design systems that need to expose live prop tables. When paired with an AI assistant, a developer can ask for “What props does the component accept?” and receive an instant, accurate answer without leaving the chat interface. The server’s lightweight Node.js implementation means it can run locally or in a container, making it suitable for both small projects and large monorepos.

Key features that set this MCP apart include:

• Zero‑touch React parsing: Built on the mature library, it understands modern JSX/TSX syntax, TypeScript type annotations, and optional default values.
• Project‑wide documentation: The tool automates the creation of a complete component reference, which can be directly embedded into documentation sites or static generators.
• Flexible integration: By exposing a standard MCP interface, the server works seamlessly with Claude Desktop, LangChain, or any other AI platform that supports Model Context Protocol.
• Extensibility: The toolset can be expanded to support additional analysis (e.g., detecting unused props, linting component conventions) without changing the MCP contract.

Typical use cases include:

1. Onboarding – New developers receive a live, searchable component guide generated on demand.
2. Component library maintenance – Automated documentation updates keep the public API docs in sync with source code.
3. AI‑powered code review – An assistant can suggest prop type improvements or warn about missing defaults during pull requests.
4. Design system synchronization – Design tools can query the MCP to verify that component props match design tokens or accessibility requirements.

By integrating react‑analyzer‑mcp into an AI workflow, developers gain a powerful ally that transforms raw React code into actionable knowledge, accelerates development cycles, and ensures consistency across large codebases.