CDK MCP Server

Integration for AWS Cloud Development Kit (CDK) best practices, infrastructure as code patterns, and security compliance with CDK Nag.

Skills

Explore the skills and capabilities of this skillset.

ExplainCDKNagRule

Explain a specific CDK Nag rule with AWS Well-Architected guidance. CDK Nag is a crucial tool for ensuring your CDK applications follow AWS security best practices. Basic implementation: ```typescript import { App } from 'aws-cdk-lib'; import { AwsSolutionsChecks } from 'cdk-nag'; const app = new App(); // Create your stack const stack = new MyStack(app, 'MyStack'); // Apply CDK Nag AwsSolutionsChecks.check(app); ``` Optional integration patterns: 1. Using environment variables: ```typescript if (process.env.ENABLE_CDK_NAG === 'true') { AwsSolutionsChecks.check(app); } ``` 2. Using CDK context parameters: ```typescript 3. Environment-specific application: ```typescript const environment = app.node.tryGetContext('environment') || 'development'; if (['production', 'staging'].includes(environment)) { AwsSolutionsChecks.check(stack); } ``` For more information on specific rule packs: - Use resource `cdk-nag://rules/{rule_pack}` to get all rules for a specific pack - Use resource `cdk-nag://warnings/{rule_pack}` to get warnings for a specific pack - Use resource `cdk-nag://errors/{rule_pack}` to get errors for a specific pack Args: ctx: MCP context rule_id: The CDK Nag rule ID (e.g., 'AwsSolutions-IAM4') Returns: Dictionary with detailed explanation and remediation steps

CDKGeneralGuidance

Use this tool to get prescriptive CDK advice for building applications on AWS. Args: ctx: MCP context

CheckCDKNagSuppressions

Check if CDK code contains Nag suppressions that require human review. Scans TypeScript/JavaScript code for NagSuppressions usage to ensure security suppressions receive proper human oversight and justification. Args: ctx: MCP context code: CDK code to analyze (TypeScript/JavaScript) file_path: Path to a file containing CDK code to analyze Returns: Analysis results with suppression details and security guidance

SearchGenAICDKConstructs

Search for GenAI CDK constructs by name or type. The search is flexible and will match any of your search terms (OR logic). It handles common variations like singular/plural forms and terms with/without spaces. Content is fetched dynamically from GitHub to ensure the most up-to-date documentation. Examples: - "bedrock agent" - Returns all agent-related constructs - "knowledgebase vector" - Returns knowledge base constructs related to vector stores - "agent actiongroups" - Returns action groups for agents - "opensearch vector" - Returns OpenSearch vector constructs The search supports subdirectory content (like knowledge bases and their sections) and will find matches across all available content. Args: ctx: MCP context query: Search term(s) to find constructs by name or description construct_type: Optional filter by construct type ('bedrock', 'opensearchserverless', etc.) Returns: Dictionary with matching constructs and resource URIs

GenerateBedrockAgentSchema

Generate OpenAPI schema for Bedrock Agent Action Groups from a file. This tool converts a Lambda file with BedrockAgentResolver into a Bedrock-compatible OpenAPI schema. It uses a progressive approach to handle common issues: 1. Direct import of the Lambda file 2. Simplified version with problematic imports commented out 3. Fallback script generation if needed Args: ctx: MCP context lambda_code_path: Path to Python file containing BedrockAgentResolver app output_path: Where to save the generated schema Returns: Dictionary with schema generation results, including status, path to generated schema, and diagnostic information if errors occurred

GetAwsSolutionsConstructPattern

Search and discover AWS Solutions Constructs patterns. AWS Solutions Constructs are vetted architecture patterns that combine multiple AWS services to solve common use cases following AWS Well-Architected best practices. Key benefits: - Accelerated Development: Implement common patterns without boilerplate code - Best Practices Built-in: Security, reliability, and performance best practices - Reduced Complexity: Simplified interfaces for multi-service architectures - Well-Architected: Patterns follow AWS Well-Architected Framework principles When to use Solutions Constructs: - Implementing common architecture patterns (e.g., API + Lambda + DynamoDB) - You want secure defaults and best practices applied automatically - You need to quickly prototype or build production-ready infrastructure This tool provides metadata about patterns. For complete documentation, use the resource URI returned in the 'documentation_uri' field. Args: ctx: MCP context pattern_name: Optional name of the specific pattern (e.g., 'aws-lambda-dynamodb') services: Optional list of AWS services to search for patterns that use them (e.g., ['lambda', 'dynamodb']) Returns: Dictionary with pattern metadata including description, services, and documentation URI

LambdaLayerDocumentationProvider

Provide documentation sources for Lambda layers. This tool returns information about where to find documentation for Lambda layers and instructs the MCP Client to fetch and process this documentation. Args: ctx: MCP context layer_type: Type of layer ("generic" or "python") Returns: Dictionary with documentation source information

Configuration

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MCP Server

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CDK MCP Server

办公文档助手
一个专为公司内部运营设计的 AI 虚拟行政助理。帮助您快速创建高质量的内部文档,如公告、会议记录、摘要、表格、流程和人力资源记录。
客服文档助手
AI 助手协助客服团队创建高质量的支持文档,包括常见问题、工单回复、道歉信和标准操作程序。引导您创建内部资源和面向客户的材料。
Google 分析师
逐步指南,教您如何将 Google Analytics 4 (GA4) 属性连接到 Google 分析师代理。涵盖创建 Google Cloud 服务账户、启用 Analytics Data API、授予 GA4 查看者访问权限,以及配置代理以支持会话、用户、跳出率、转换等指标。非常适合快速在 Bika.ai 中设置 GA4 数据报告。
X/Twitter 助手
一个 AI 驱动的 Twitter 助手,帮助内容创作者将 AI 产品体验转化为病毒式推文 - 具有自动润色、智能研究和一键发布功能。
Github issues 助手
Github Issues 助手是一个 AI 智能体,用于简化 GitHub issues的管理。它可以直接在存储库中简化创建、跟踪和优先处理错误、任务或功能请求的过程。非常适合团队使用,确保一致的格式,自动化重复步骤,并与开发管道集成。
品牌设计师
一款专为初创数字产品设计的品牌营销 AI 助手,帮助您快速生成适合 Product Hunt、AppSumo 等平台的在线推广材料,涵盖视觉创意、推广标语、品牌语调和卖点传达
需求文档撰写助手
告诉我您的产品或功能想法 - 我将帮助您创建全面且详细的需求文档,涵盖用户故事、验收标准、技术规范等内容。
社区活动分析员
分析社区活动截图,报告参与趋势和讨论亮点。上传社区互动的截图,该智能体会生成一份清晰的markdown报告,总结参与水平、关键讨论主题和显著亮点 — 非常适合社区经理、市场营销人员和产品团队。
Email 营销助手
自动寻找潜在客户并发送为期3天的跟进邮件序列。

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