This React Native MCP server exhibits significant quality gaps across naming, descriptions, and schema completeness. While tool names generally use verb-noun patterns (analyze_component, upgrade_packages), descriptions lack LLM-optimization guidance and many parameters are underdescribed. Most critically, the actual tool implementations are not visible in the provided source, only tool registration calls are shown in src/tools/index.ts without implementation details. This forces inference-based scoring, which caps tool scores. Schemas exist but are sparse; no output schemas are documented. Parameter descriptions are present but generic (e.g., 'Path to React Native project root' repeated across many tools without guidance on format or validation). Error handling patterns are absent from visible code. The server registers 10 tools but lacks composition clarity, several tools overlap in scope (analyze_component, analyze_codebase_comprehensive, analyze_codebase_performance) without clear differentiation guidance for LLM selection.

• Publish complete tool implementation source (src/tools/index.ts) showing actual function bodies, error handling, and return value schemas. Validation requires seeing how parameters are processed and what is returned.
• Add output schema documentation to each tool description. Example: 'Returns {findings: [{type: string, severity: string, location: string, suggestion: string}], summary: {total_issues: number, by_severity: object}}'. This enables LLMs to extract and plan around results.
• Rewrite parameter descriptions to be LLM-optimized. For project_path: 'Absolute or relative path to the root of the React Native project (e.g., /home/user/my-app or ./project). Must contain package.json and node_modules.'
• Add WHEN to use guidance in tool descriptions. Example for analyze_component vs analyze_codebase_comprehensive: 'Use analyze_component to inspect a single component's best practices. Use analyze_codebase_comprehensive for a full-project audit including performance, security, refactoring, and accessibility.'
• Implement dry-run patterns for mutating tools. upgrade_packages should support a dry_run=true mode that returns what would be upgraded without applying changes. Document rollback steps if auto_apply=true.
• Add error classification to tool descriptions: 'Returns retryable errors (e.g., network timeout) vs user-fixable errors (e.g., invalid project path) vs fatal errors (e.g., incompatible Node version). Includes recovery suggestions in each error response.'
• Document pagination for large-result tools. E.g., analyze_codebase_comprehensive should return {findings: [...max 50 items], total_findings: number, has_more: boolean, next_page_token: string}. Include limit parameter with range (1-100, default 50).