@versatil/sdlc-framework
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🚀 AI-Native SDLC framework with 11-MCP ecosystem, RAG memory, OPERA orchestration, and 6 specialized agents achieving ZERO CONTEXT LOSS. Features complete CI/CD pipeline with 7 GitHub workflows (MCP testing, security scanning, performance benchmarking),
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TypeScript
/**
* Vertex AI MCP Executor
* ✅ PRODUCTION IMPLEMENTATION - Google Cloud Vertex AI + Gemini Integration
*
* Primary Agents: Dr.AI-ML (ML training, deployment), Marcus-Backend (AI API integration)
*
* Features:
* - Gemini model inference (text, code, multimodal)
* - Model deployment and management
* - AI model monitoring and optimization
* - Vertex AI Platform integration
* - Custom model training support
*
* Official Packages:
* - @google-cloud/vertexai (official Google Cloud SDK)
* - @google-cloud/aiplatform (platform management)
* - vertex-ai-mcp-server (MCP server implementation)
*/
export interface MCPExecutionResult {
success: boolean;
data?: any;
error?: string;
metadata?: {
model?: string;
timestamp?: string;
usage?: {
promptTokens?: number;
completionTokens?: number;
totalTokens?: number;
};
[key: string]: any;
};
}
export declare class VertexAIMCPExecutor {
private vertexAI;
private projectId;
private location;
constructor();
/**
* Initialize Vertex AI client
*/
private initializeVertexAI;
/**
* Execute Vertex AI MCP action
* Routes to appropriate Vertex AI operation based on action type
*/
executeVertexAIMCP(action: string, params?: any): Promise<MCPExecutionResult>;
/**
* Generate text using Gemini model
*/
private generateText;
/**
* Generate code using Gemini Code model
*/
private generateCode;
/**
* Analyze code for issues, improvements, security vulnerabilities
*/
private analyzeCode;
/**
* Multi-turn chat conversation
*/
private chat;
/**
* Generate text embeddings for semantic search
*/
private generateEmbeddings;
/**
* Deploy ML model to Vertex AI Platform
*/
private deployModel;
/**
* Make prediction using deployed model
*/
private predict;
/**
* Get available Gemini models
*/
listModels(): Promise<string[]>;
/**
* Cleanup resources
*/
close(): Promise<void>;
}
export declare const vertexAIMCPExecutor: VertexAIMCPExecutor;