Skip to main content
Glama
MrNitro360

React Native MCP Server

by MrNitro360
OverviewSchemaRelated ServersScoreDiscussions
TypeScript

React Native MCP Server

npm version License: MIT Model Context Protocol Auto-Deploy TypeScript React Native

Professional AI-powered React Native development companion with expert-level code remediation

Expert remediation • Automated fixes • Industry best practices • Enterprise security

Overview

A comprehensive Model Context Protocol (MCP) server designed for professional React Native development teams. This tool provides intelligent code analysis, expert-level automated code remediation, security auditing, and performance optimization with production-ready fixes.

🆕 v1.1.0 - Expert Remediation Features:

  • 🔧 Expert Code Remediation - Automatically fix security, performance, and quality issues

  • 🏗️ Advanced Refactoring - Comprehensive component modernization and optimization

  • 🛡️ Security Fixes - Automatic hardcoded secret migration and vulnerability patching

  • ⚡ Performance Fixes - Memory leak prevention and React Native optimization

  • 📝 Production-Ready Code - TypeScript interfaces, StyleSheet extraction, accessibility

Key Benefits:

  • 🚀 Accelerated Development - Automated code analysis, fixing, and test generation

  • 🔒 Enterprise Security - Vulnerability detection with automatic remediation

  • 📊 Quality Assurance - Industry-standard testing frameworks and coverage analysis

  • ⚡ Performance Optimization - Advanced profiling with automatic fixes

  • 🎯 Best Practices - Expert guidance with code implementation

  • 🔄 Automated Updates - Continuous integration with automatic version management

Related MCP server: React Native Expo MCP

Quick Start

Prerequisites

  • Node.js 18.0 or higher

  • Claude CLI or Claude Desktop

  • React Native development environment

Installation

Automated Installation (Recommended)

# Install globally via npm
npm install -g @mrnitro360/react-native-mcp-guide

# Configure with Claude CLI
claude mcp add react-native-guide npx @mrnitro360/react-native-mcp-guide

Development Installation

# Clone repository
git clone https://github.com/MrNitro360/React-Native-MCP.git
cd React-Native-MCP

# Install dependencies and build
npm install && npm run build

# Add to Claude CLI
claude mcp add react-native-guide node ./build/index.js

Verification

claude mcp list

Verify that react-native-guide appears as Connected ✅

🆕 Expert Remediation Examples

Before vs. After: Automatic Code Fixing

❌ Before (Problematic Code):

const MyComponent = () => {
  const apiKey = "sk-1234567890abcdef"; // Hardcoded secret
  const [data, setData] = useState([]);
  
  useEffect(() => {
    console.log("API Key:", apiKey); // Sensitive logging
    fetch('http://api.example.com/data') // HTTP instead of HTTPS
      .then(response => response.json())
      .then(data => setData(data));
      
    const interval = setInterval(() => { // Memory leak
      console.log('Polling...');
    }, 1000);
  }, []);

  return (
    <ScrollView>
      {data.map(item => ( // Performance issue
        <Text key={item.id} style={{color: 'red'}}>{item.name}</Text>
      ))}
    </ScrollView>
  );
};

✅ After (Expert Remediation):

interface Props {
  children?: React.ReactNode;
  onPress?: () => void;
}

const MyComponent: React.FC<Props> = () => {
  // TODO: Add API_KEY to your environment variables
  const apiKey = process.env.API_KEY || Config.API_KEY;
  const [data, setData] = useState([]);
  
  useEffect(() => {
    // Removed sensitive logging for security
    // console.log('[REDACTED - contains sensitive data]');
    
    // Upgraded to HTTPS for security
    fetch('https://api.example.com/data')
      .then(response => response.json())
      .then(data => setData(data));
      
    const interval = setInterval(() => {
      console.log('Polling...');
    }, 1000);
    
    // Cleanup intervals to prevent memory leaks
    return () => {
      clearInterval(interval);
    };
  }, []);

  return (
    <FlatList
      data={data}
      keyExtractor={(item, index) => item.id?.toString() || index.toString()}
      renderItem={({ item }) => (
        <Text style={styles.itemText}>{item.name}</Text>
      )}
    />
  );
};

const styles = StyleSheet.create({
  itemText: {
    color: 'red'
  }
});

export default React.memo(MyComponent);

🎯 What Got Fixed Automatically:

  • ✅ Security: Hardcoded API key → Environment variable

  • ✅ Security: Sensitive logging → Sanitized

  • ✅ Security: HTTP → HTTPS upgrade

  • ✅ Performance: ScrollView + map → FlatList with keyExtractor

  • ✅ Memory: Added interval cleanup to prevent leaks

  • ✅ Best Practices: Inline styles → StyleSheet.create

  • ✅ Type Safety: Added TypeScript interface

  • ✅ Performance: Wrapped with React.memo

Core Features

🔧 Expert Code Remediation (NEW in v1.1.0)

Tool

Capability

Level

Output

remediate_code

Automatic security, performance, and quality fixes

Expert

Production-ready code

refactor_component

Advanced component modernization and optimization

Senior

Refactored components with tests

Security Remediation

Hardcoded secrets → environment variables

Enterprise

Secure code patterns

Performance Fixes

Memory leaks, FlatList optimization, StyleSheet

Expert

Optimized components

Type Safety

Automatic TypeScript interface generation

Professional

Type-safe code

🧪 Advanced Testing Suite

Feature

Description

Frameworks

Automated Test Generation

Industry-standard test suites for components

Jest, Testing Library

Coverage Analysis

Detailed reports with improvement strategies

Jest Coverage, LCOV

Strategy Evaluation

Testing approach analysis and recommendations

Unit, Integration, E2E

Framework Integration

Multi-platform testing support

Detox, Maestro, jest-axe

🔍 Comprehensive Analysis Tools

Analysis Type

Capabilities

Output

Security Auditing

Vulnerability detection with auto-remediation

Risk-prioritized reports + fixes

Performance Profiling

Memory, rendering, bundle optimization + fixes

Actionable recommendations + code

Code Quality

Complexity analysis with refactoring implementation

Maintainability metrics + fixes

Accessibility

WCAG compliance with automatic improvements

Compliance reports + code

📦 Dependency Management

  • Automated Package Auditing - Security vulnerabilities and outdated dependencies

  • Intelligent Upgrades - React Native compatibility validation

  • Conflict Resolution - Dependency tree optimization

  • Migration Assistance - Deprecated package modernization

📚 Expert Knowledge Base

  • React Native Documentation - Complete API references and guides

  • Architecture Patterns - Scalable application design principles

  • Platform Guidelines - iOS and Android specific best practices

  • Security Standards - Mobile application security frameworks

Usage Examples

🔧 Expert Code Remediation (NEW)

# Automatically fix all detected issues with expert-level solutions
claude "remediate_code with remediation_level='expert' and add_comments=true"

# Advanced component refactoring with performance optimization
claude "refactor_component with refactor_type='comprehensive' and include_tests=true"

# Security-focused remediation
claude "remediate_code with issues=['hardcoded_secrets', 'sensitive_logging'] and remediation_level='expert'"

# Performance-focused refactoring
claude "refactor_component with refactor_type='performance' and target_rn_version='latest'"

Testing & Quality Assurance

# Generate comprehensive component tests
claude "generate_component_test with component_name='LoginForm' and test_type='comprehensive'"

# Analyze testing strategy
claude "analyze_testing_strategy with focus_areas=['unit', 'accessibility', 'performance']"

# Generate coverage report
claude "analyze_test_coverage with coverage_threshold=85"

Code Analysis & Optimization

# Comprehensive codebase analysis with auto-remediation suggestions
claude "analyze_codebase_comprehensive"

# Performance optimization with specific focus areas
claude "analyze_codebase_performance with focus_areas=['memory_usage', 'list_rendering']"

# Security audit with vulnerability detection
claude "analyze_codebase_comprehensive with analysis_types=['security', 'performance']"

Dependency Management

# Package upgrade recommendations
claude "upgrade_packages with update_level='minor'"

# Resolve dependency conflicts
claude "resolve_dependencies with fix_conflicts=true"

# Security vulnerability audit
claude "audit_packages with auto_fix=true"

Real-World Scenarios

Scenario

Command

Outcome

🔧 Automatic Code Fixing

"Fix all security and performance issues in my component with expert solutions"

Production-ready remediated code

🏗️ Component Modernization

"Refactor my legacy component to modern React Native patterns with tests"

Modernized component + test suite

🛡️ Security Hardening

"Automatically fix hardcoded secrets and security vulnerabilities"

Secure code with environment variables

⚡ Performance Optimization

"Fix memory leaks and optimize FlatList performance automatically"

Optimized code with cleanup

📝 Type Safety Enhancement

"Add TypeScript interfaces and improve type safety automatically"

Type-safe code with interfaces

Pre-deployment Security Check

"Scan my React Native project for security vulnerabilities"

Security report + automatic fixes

Performance Bottleneck Analysis

"Analyze my app for performance bottlenecks and memory leaks"

Optimization roadmap + fixes

Code Quality Review

"Review my codebase for refactoring opportunities"

Quality improvement + implementation

Accessibility Compliance

"Check my app for accessibility issues and fix them automatically"

WCAG compliance + code fixes

Component Test Generation

"Generate comprehensive tests for my LoginScreen component"

Complete test suite

Testing Strategy Optimization

"Analyze my current testing strategy and suggest improvements"

Testing roadmap

Claude Desktop Integration

NPM Installation Configuration

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "react-native-guide": {
      "command": "npx",
      "args": ["@mrnitro360/react-native-mcp-guide@1.1.0"],
      "env": {}
    }
  }
}

Development Configuration

{
  "mcpServers": {
    "react-native-guide": {
      "command": "node",
      "args": ["/absolute/path/to/React-Native-MCP/build/index.js"],
      "env": {}
    }
  }
}

Configuration Paths:

  • Windows: C:\Users\{Username}\Desktop\React-Native-MCP\build\index.js

  • macOS/Linux: /Users/{Username}/Desktop/React-Native-MCP/build/index.js

Development & Maintenance

Local Development

# Development with hot reload
npm run dev

# Production build
npm run build

# Production server
npm start

Continuous Integration

This project implements enterprise-grade CI/CD:

  • ✅ Automated Version Management - Semantic versioning with auto-increment

  • ✅ Continuous Deployment - Automatic npm publishing on merge

  • ✅ Release Automation - GitHub releases with comprehensive changelogs

  • ✅ Quality Gates - Build validation and testing before deployment

Update Management

# Check current version
npm list -g @mrnitro360/react-native-mcp-guide

# Update to latest version
npm update -g @mrnitro360/react-native-mcp-guide

# Reconfigure Claude CLI
claude mcp remove react-native-guide
claude mcp add react-native-guide npx @mrnitro360/react-native-mcp-guide

Technical Specifications

🎯 Analysis & Remediation Capabilities

  • Expert Code Remediation - Automatic fixing of security, performance, and quality issues

  • Advanced Component Refactoring - Comprehensive modernization with test generation

  • Comprehensive Codebase Analysis - Multi-dimensional quality assessment with fixes

  • Enterprise Security Auditing - Vulnerability detection with automatic remediation

  • Performance Intelligence - Memory, rendering, and bundle optimization with fixes

  • Quality Metrics - Complexity analysis with refactoring implementation

  • Accessibility Compliance - WCAG 2.1 AA standard validation with automatic fixes

  • Testing Strategy Optimization - Coverage analysis and framework recommendations

🛠️ Technical Architecture

  • 12 Specialized Tools - Complete React Native development lifecycle coverage + remediation

  • 2 Expert Remediation Tools - remediate_code and refactor_component

  • 6 Expert Prompt Templates - Structured development workflows

  • 5 Resource Libraries - Comprehensive documentation and best practices

  • Industry-Standard Test Generation - Automated test suite creation

  • Multi-Framework Integration - Jest, Detox, Maestro, and accessibility tools

  • Real-time Coverage Analysis - Detailed reporting with improvement strategies

  • Production-Ready Code Generation - Expert-level automated fixes and refactoring

🏢 Enterprise Features

  • Expert-Level Remediation - Senior engineer quality automatic code fixes

  • Production-Ready Solutions - Enterprise-grade security and performance fixes

  • Professional Reporting - Executive-level summaries with implementation code

  • Security-First Architecture - Comprehensive vulnerability assessment with fixes

  • Scalability Planning - Large-scale application design patterns with refactoring

  • Compliance Support - Industry standards with automatic compliance fixes

  • Multi-Platform Optimization - iOS and Android specific considerations with fixes

📋 Changelog

v1.1.0 - Expert Code Remediation (Latest)

🚀 Major Features:

  • ✨ NEW: remediate_code tool - Expert-level automatic code fixing

  • ✨ NEW: refactor_component tool - Advanced component refactoring with tests

  • 🔧 Enhanced: Component detection accuracy improved

  • 🛡️ Security: Automatic hardcoded secret remediation

  • ⚡ Performance: Memory leak prevention and FlatList optimization

  • 📝 Quality: TypeScript interface generation and StyleSheet extraction

  • 🎯 Accessibility: WCAG compliance with automatic fixes

🎯 Remediation Capabilities:

  • Hardcoded secrets → Environment variables

  • Sensitive logging → Sanitized code

  • HTTP requests → HTTPS enforcement

  • Memory leaks → Automatic cleanup

  • Inline styles → StyleSheet.create

  • Performance issues → Optimized patterns

  • Type safety → TypeScript interfaces

v1.0.5 - Previous Version

  • Comprehensive analysis tools

  • Testing suite generation

  • Dependency management

  • Performance optimization guidance

Support & Community

Resources

Contributing

We welcome contributions from the React Native community. Please review our Contributing Guidelines for development standards and submission processes.

License

This project is licensed under the MIT License. See the license file for detailed terms and conditions.

Professional React Native Development with Expert-Level Remediation

Empowering development teams to build secure, performant, and accessible mobile applications with automated expert-level code fixes

🆕 v1.1.0 - Now with Expert Code Remediation!

Get Started • Documentation • Community

Available Tools

13 tools
analyze_codebase_comprehensiveC

Comprehensive React Native codebase analysis including performance, security, refactoring, and upgrades

ParametersJSON Schema
NameRequiredDescriptionDefault
codebase_pathNoPath to React Native project root
analysis_typesNoTypes of analysis to perform

TDQS

C2.8/5.0
Behavior1/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It only lists analysis types but does not indicate whether the tool is read-only, if it modifies the codebase, what side effects exist, or how long execution might take.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence, which is concise but lacks structure. It is front-loaded with the tool's purpose, but subsequent details are missing. It earns its place but could be more informative without becoming verbose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's broad scope and lack of output schema or annotations, the description is incomplete. It does not explain what the analysis produces (e.g., a report), how to interpret results, or any prerequisites like project initialization. For a 'comprehensive' tool, more context is needed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the schema already documents both parameters adequately. The description adds little beyond the schema, only listing example analysis types which are already in the enum. Thus, it meets the baseline but does not enhance understanding.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'analyze' and the resource 'codebase' with a comprehensive scope, listing specific areas like performance, security, refactoring, and upgrades. This distinguishes it from more specific sibling tools such as 'analyze_codebase_performance'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description lacks any guidance on when to use this comprehensive analysis versus the more targeted sibling tools. It does not mention prerequisites, when not to use it, or alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

analyze_codebase_performanceB

Analyze entire React Native codebase for performance issues

ParametersJSON Schema
NameRequiredDescriptionDefault
codebase_pathNoPath to React Native project root
focus_areasNoSpecific performance areas to focus on

TDQS

B3/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided; the description does not disclose behavioral traits such as whether it performs static analysis, runs the app, or takes time. It merely states the action without explaining consequences or side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence, which is concise but lacks structure and fails to convey essential guidance. It could be improved with more detail while remaining succinct.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema and no annotations, the description is incomplete. It does not explain what the analysis returns, prerequisites, or how it interacts with the codebase. Sibling tools provide related but different functionalities.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with descriptions for both parameters, so the description adds no additional meaning beyond what the schema already provides. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('analyze') and resource ('entire React Native codebase') with a clear focus on performance issues. It distinguishes from sibling 'analyze_codebase_comprehensive' which likely covers broader aspects.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives like 'analyze_component' or 'optimize_performance'. The description lacks explicit context for selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

analyze_componentC

Analyze React Native component for best practices

ParametersJSON Schema
NameRequiredDescriptionDefault
codeNoReact Native component code to analyze. If not provided, analyzes entire codebase
typeNoComponent type
codebase_pathNoPath to React Native project root for codebase analysis

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description must disclose behavioral traits. It only states 'analyze for best practices' without mentioning whether the tool is read-only, requires permissions, or produces side effects. Key gaps for a non-annotated tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single, direct sentence that succinctly states the tool's purpose without any extraneous information. Efficient and to the point.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite 3 parameters and no output schema, the description does not explain what the analysis yields or how results are presented. Sibling tools suggest specialized analyses, but this description lacks sufficient context for an agent to understand its scope.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, providing adequate descriptions for all parameters. The tool description adds no additional context beyond the schema, so it meets the baseline but does not exceed it.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'analyze' and the resource 'React Native component', indicating the tool's function. However, it does not differentiate from sibling tools like 'analyze_codebase_comprehensive' or 'analyze_codebase_performance', which may cause confusion.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool vs. alternatives. It does not specify context, prerequisites, or exclusion criteria, leaving the agent to infer without support.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

analyze_test_coverageB

Analyze test coverage and identify gaps

ParametersJSON Schema
NameRequiredDescriptionDefault
project_pathNoPath to React Native project root
coverage_thresholdNoMinimum coverage threshold percentage
generate_reportNoGenerate detailed coverage report

TDQS

B3.1/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, and the description does not disclose behavioral traits such as whether it modifies the codebase, required permissions, or run time. The bare description fails to inform the agent of side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Extremely concise single sentence with no filler. However, it might be too brief; a small expansion could improve usefulness without harming conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite well-documented parameters, the lack of output schema and absence of any description about return value or report format leaves the tool incomplete for an agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Input schema provides 100% coverage with descriptions for all three parameters. The description adds no additional meaning beyond what the schema offers, but the schema is sufficient.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Analyze test coverage and identify gaps' clearly states the verb (analyze) and resource (test coverage), and distinguishes from sibling tools like 'analyze_codebase_comprehensive' or 'analyze_testing_strategy'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when or when not to use this tool, nor any mention of alternatives. The description is too minimal to aid decision-making.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

analyze_testing_strategyC

Analyze current testing strategy and provide recommendations

ParametersJSON Schema
NameRequiredDescriptionDefault
project_pathNoPath to React Native project root
focus_areasNoAreas to focus testing analysis on

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided; description does not disclose whether the tool is read-only, modifies anything, or requires specific permissions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Single concise sentence; efficient but could benefit from slightly more detail without becoming verbose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Description is minimal for a tool with two parameters and no output schema; lacks information on what the recommendations look like or how to interpret results.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3; description adds no extra meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states verb 'Analyze' and resource 'testing strategy', and it is distinct from sibling tools like 'analyze_test_coverage' which is more specific.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives such as 'generate_component_test' or 'analyze_test_coverage'.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

architecture_adviceC

Get React Native architecture and project structure advice

ParametersJSON Schema
NameRequiredDescriptionDefault
project_typeYesType of React Native project
featuresNoKey features of the app

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, and the description does not disclose behavioral traits such as side effects, return format, or required permissions. The tool is likely read-only but this is not explicitly stated.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that directly conveys the purpose. It is appropriately concise, though it could include a bit more detail without becoming verbose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema and no annotations, the description should compensate by explaining what the advice looks like or how parameters affect it. It fails to do so, leaving significant gaps in the agent's understanding of the tool's behavior.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The description does not add any additional meaning beyond what the schema already provides for 'project_type' and 'features'.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Get') and the domain ('React Native architecture and project structure advice'). It distinguishes itself from sibling analysis tools by focusing on advice rather than analysis, but could be more specific about what kind of advice is provided.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives (e.g., analyze_codebase_comprehensive). No prerequisites or exclusions are mentioned, leaving the agent to infer usage context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

check_for_updatesA

Check for available updates to the React Native MCP server

ParametersJSON Schema
NameRequiredDescriptionDefault
include_changelogNoInclude changelog in the response

TDQS

A3.5/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden. It communicates a read-only operation, but does not disclose what the response looks like (e.g., whether it returns a list of updates or just a boolean) or any side effects. It is adequate but lacks depth.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence of 10 words, front-loading the core action. Every word earns its place with no extraneous information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple check tool with one optional parameter and no output schema, the description is adequate. However, it does not explain what the tool returns (e.g., available updates or 'no updates') or handle potential failures, leaving some ambiguity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema covers 100% of the parameters (one boolean, include_changelog, with its own description). The tool description adds no extra meaning beyond what the schema already provides, so a baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'check' and the resource 'available updates to the React Native MCP server', making the purpose unmistakable. It distinguishes itself from sibling tools that focus on analysis, debugging, or refactoring.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives. The description does not mention any context, prerequisites, or situations where this tool is appropriate or not.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

debug_issueB

Get debugging guidance for React Native issues

ParametersJSON Schema
NameRequiredDescriptionDefault
issue_typeYesType of issue to debug
platformNoPlatform where issue occurs
error_messageNoError message if available

TDQS

B3.4/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden for behavioral transparency. It only states 'Get debugging guidance' without disclosing whether it modifies state, requires permissions, or has side effects. This is a gap for a tool that likely returns information.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence of 6 words, which is extremely concise and front-loaded. It contains no unnecessary words and is appropriate for the tool's simplicity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema and no annotations, the description is incomplete. It does not explain what the guidance looks like, nor does it provide context about response format or behavior, leaving the agent underinformed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 100% description coverage for all three parameters, so the description does not need to add much. It adds no additional meaning beyond what is already in the schema, which is acceptable.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Get debugging guidance for React Native issues', which is a specific verb and resource. It distinguishes itself from sibling tools like 'analyze_codebase_comprehensive' or 'refactor_component' by focusing on debugging guidance.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies use when debugging React Native issues but provides no explicit guidance on when not to use it or alternatives. It is minimally viable but lacks any usage context or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

generate_component_testB

Generate comprehensive React Native component tests following industry best practices

ParametersJSON Schema
NameRequiredDescriptionDefault
component_codeYesReact Native component code to generate tests for
component_nameYesName of the component
test_typeNoType of tests to generatecomprehensive
testing_frameworkNoTesting framework preferencejest
include_accessibilityNoInclude accessibility tests
include_performanceNoInclude performance tests
include_snapshotNoInclude snapshot tests

TDQS

B3.1/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description provides no behavioral details such as side effects, permissions required, or whether the tool is read-only. It only states the task without explaining what happens beyond generation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single, efficient sentence with no wasted words. However, it lacks structural elements like bullet points that could improve readability at a glance.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description does not mention the tool's output (e.g., generated test code) or return format. Given the lack of an output schema, this is a significant gap for completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

All 7 parameters have descriptions in the input schema (100% coverage), so the description adds no extra meaning. Baseline 3 is appropriate as the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's verb ('generate'), resource ('React Native component tests'), and scope ('comprehensive following industry best practices'). It effectively distinguishes from sibling tools that analyze or debug rather than generate.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives like analyze_test_coverage. No prerequisites or exclusions are mentioned, leaving the agent to infer usage context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_version_infoB

Get React Native MCP Server version and build information

ParametersJSON Schema
NameRequiredDescriptionDefault
include_build_infoNoInclude detailed build information

TDQS

B3.4/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden for behavioral disclosure. It only states the function without detailing side effects, authorization needs, or data freshness. For a read tool, this is thin.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence with no superfluous words. It is appropriately sized for the tool's simplicity and front-loads the purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, so the description should help understand return values. It mentions 'version and build information' but does not specify their structure or content, leaving the agent with incomplete context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage for its single parameter. The description adds no extra meaning beyond what the schema already provides, so a baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool retrieves version and build information for the server. It uses a specific verb ('Get') and resource, and distinguishes from sibling tools that focus on analysis and debugging.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool versus alternatives is provided. The usage is implied by the simplicity of the task, but the description lacks when-not or alternative references.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

optimize_performanceC

Get performance optimization suggestions for React Native

ParametersJSON Schema
NameRequiredDescriptionDefault
scenarioYesPerformance scenario to optimize
platformNoTarget platform

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations exist, so the description bears full responsibility for disclosing behavior. It only states the basic function without mentioning whether the tool is read-only, what data it accesses, or any side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single clear sentence with no redundant words. It is efficiently front-loaded but could be slightly more detailed without losing conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description is minimal for a tool with 2 parameters, no output schema, and no annotations. It does not explain return format, how suggestions are generated, or any constraints, leaving significant gaps for an agent to use it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with each parameter having a description. The description adds 'React Native' context not in the schema, providing slight added meaning. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Get' and resource 'performance optimization suggestions' with the scope 'React Native'. It distinguishes from siblings like analyze_codebase_performance which likely analyzes performance rather than providing suggestions, but does not explicitly differentiate.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives such as analyze_codebase_performance. The description does not specify context or prerequisites for using the tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

refactor_componentC

Provide expert-level refactoring suggestions and implementations

ParametersJSON Schema
NameRequiredDescriptionDefault
codeYesReact Native component code to refactor
refactor_typeYesType of refactoring to apply
target_rn_versionNoTarget React Native version for refactoring
include_testsNoWhether to include test updates

TDQS

C2.5/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description must disclose behavioral traits. It only says 'provide expert-level refactoring suggestions and implementations' without stating important aspects: whether it returns code diffs or explanations, whether it modifies files, if it requires authentication, or any side effects. This is insufficient for an AI agent to anticipate behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence, making it concise. However, it is too vague to be fully effective; a more specific sentence of similar length could be more informative. It is not overly long, but it sacrifices completeness for brevity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (component refactoring with multiple types), the description lacks details about what the agent will receive as output (since no output schema exists), how the refactoring is presented, or any prerequisites. The 4-parameter schema is fully described, but the description does not complement it with higher-level context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so each parameter is already documented by the schema. The description adds no further meaning or context about the parameters (e.g., valid values for 'target_rn_version' or what 'include_tests' entails). Baseline 3 is appropriate as schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the tool provides 'expert-level refactoring suggestions and implementations', which is a clear verb+resource goal. However, it does not differentiate from sibling tools like 'analyze_component' or 'remediate_code', and the scope (component-level) is only implied by the name, not restated in the description.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives, such as when to prefer 'refactor_component' over 'remediate_code' or 'analyze_component'. There are no usage conditions, prerequisites, or exclusions mentioned.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

remediate_codeC

Automatically fix React Native code issues with expert-level solutions

ParametersJSON Schema
NameRequiredDescriptionDefault
codeYesReact Native code to remediate
issuesNoSpecific issues to fix (if not provided, auto-detects all)
remediation_levelNoLevel of remediation to apply
preserve_formattingNoWhether to preserve original code formatting
add_commentsNoWhether to add explanatory comments to fixes

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must disclose behavioral traits. 'Automatically fix' suggests mutation, but it does not explain side effects (e.g., formatting changes, comment addition) or limitations (e.g., only specific issue patterns). The brevity leaves agents unaware of potential outcomes.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, direct sentence that efficiently communicates the tool's purpose. It is front-loaded and avoids redundancy, though it could expand on key details without harming conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of 5 parameters and no output schema, the description is inadequate. It does not specify return values (expected to be fixed code) or any other output format, leaving agents without complete context to assess the tool's utility.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema provides 100% description coverage for all 5 parameters, so the schema already explains each parameter's purpose. The description adds no further detail, meeting the baseline for this dimension.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('fix') and resource ('React Native code issues') with 'expert-level solutions', which conveys a direct remediation capability. It distinguishes from sibling tools that analyze or debug without fixing. However, it could be more specific about the types of issues addressed.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool versus alternatives like debug_issue or refactor_component. The description implies usage for known issues but does not clarify scenarios where auto-fixing is appropriate or contraindicated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. 13 tool updates
    • First observedanalyze_codebase_comprehensive
    • First observedanalyze_codebase_performance
    • First observedanalyze_component
    • First observedanalyze_test_coverage
    • First observedanalyze_testing_strategy
    • First observedarchitecture_advice
    • First observedcheck_for_updates
    • First observeddebug_issue
    • First observedgenerate_component_test
    • First observedget_version_info
    • First observedoptimize_performance
    • First observedrefactor_component
    • First observedremediate_code
Install Server
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

TDQS

C2.9/5.0
Disambiguation2/5

Multiple tools have overlapping purposes that could cause confusion. For example, analyze_codebase_comprehensive includes performance analysis, but there is also a separate analyze_codebase_performance tool, and optimize_performance seems to cover similar ground. Similarly, refactor_component and remediate_code both involve fixing or improving code, making it unclear when to use each. While descriptions provide some differentiation, the boundaries between tools are fuzzy, leading to potential misselection.

Naming Consistency3/5

The naming follows a mixed convention with some consistency but notable deviations. Most tools use a verb_noun pattern (e.g., analyze_codebase_performance, generate_component_test), which is readable. However, there are inconsistencies like check_for_updates (verb_preposition_noun) and get_version_info (verb_noun_noun), and the use of underscores is consistent but the verb styles vary. Overall, it's a mixed bag that doesn't follow a strict pattern but remains somewhat coherent.

Tool Count4/5

With 13 tools, the count is reasonable for a React Native development server, falling within the typical well-scoped range of 3-15 tools. Each tool appears to serve a distinct aspect of React Native development, such as analysis, debugging, testing, and optimization, suggesting they earn their place. However, some overlap in functionality might indicate slight bloat, but it's not excessive.

Completeness4/5

The tool surface covers key areas of React Native development, including code analysis, performance, testing, debugging, and refactoring, with no obvious dead ends. Minor gaps exist, such as a lack of tools for deployment or integration with external services, but agents can likely work around these. The coverage is comprehensive for core development workflows, though not exhaustive for all possible scenarios in the domain.

Maintenance

ActivityInactive
ResponsivenessUnresponsive

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Related MCP Connectors

Related MCP Servers

  • React Native Expo MCP

    ZaharGusyatin
    F
    license
    A
    quality
    D
    maintenance
    An MCP server designed for React Native and Expo development that provides specialized tools for project scaffolding, architectural best practices, and troubleshooting. It enables AI assistants to guide users through setup, navigation configuration, and CI/CD processes using modern stacks like NativeWind and Zustand.
    13
    4
    -

  • react-native-toolkit

    ItamiForge
    A
    license
    A
    quality
    C
    maintenance
    Provides AI agents with accurate, version-aware documentation for React Native, Expo, React Navigation, and Ignite by automatically detecting project dependencies and fetching matching documentation.
    12
    MIT

Appeared in Searches

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/MrNitro360/React-Native-MCP'

If you have feedback or need assistance with the MCP directory API, please join our Discord server