[Feature Request] Complete BAR (Backup and Restore) Tools Implementation for DSA Integration

[Asimz4321]

🎯 Feature Request: Complete BAR Tools Implementation

Summary

Implement a comprehensive suite of BAR (Backup and Restore) tools to integrate AI agents with Teradata DSA (Data Stream Architecture) for enterprise-grade backup management across multiple storage solutions.

Current Status

• ✅ Foundation Complete: bar_manageDsaDiskFileSystem tool implemented and tested
• ✅ Architecture Documented: DSA integration diagram and comprehensive documentation
• 🚧 15 Additional Tools Planned: Complete multi-cloud and enterprise storage support

Proposed Implementation

🏗️ Architecture Overview

The BAR tools will provide AI agents with direct access to Teradata DSA backup operations through a layered architecture:

flowchart TD
    %% AI Agent Layer
    User[👤 User] --> LLM[🤖 AI Agent] --> Output[📄 Output]
    
    %% MCP Integration
    LLM --> MCP[🔌 MCP Server]
    MCP --> API[🌐 DSA API]
    API --> DSC[🎛️ DSC]
    
    %% DSA Infrastructure
    DSC --> DSMain[📊 DSMain]
    DSC --> BarNC[📦 BarNC]
    
    %% Data Flow
    DB[(🗄️ Database)] <--> DSMain
    DSMain <--> BarNC
    BarNC --> Storage{💾 Storage}
    
    %% Storage Options
    Storage --> Disk[📁 Disk]
    Storage --> Cloud[☁️ Cloud]
    Storage --> Enterprise[🔒 Enterprise]
    
    %% Styling
    classDef primary fill:#e3f2fd,stroke:#1976d2
    classDef secondary fill:#f3e5f5,stroke:#7b1fa2
    classDef storage fill:#e8f5e8,stroke:#388e3c
    
    class User,LLM,Output primary
    class MCP,API,DSC secondary
    class DSMain,BarNC,DB,Storage,Disk,Cloud,Enterprise storage

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📋 Total Estimated Tools 16 (1 ✅ Developed, 15 🚧 Planned)

Storage Configuration Tools (6/16)

• bar_manageDsaDiskFileSystem ✅ Implemented
• bar_manageAwsS3 - AWS S3 bucket configurations
• bar_manageAzureBlob - Azure Blob Storage configurations
• bar_manageGoogleCloud - Google Cloud Storage configurations
• bar_manageNetBackup - NetBackup enterprise storage
• bar_manageIbmSpectrum - IBM Spectrum Protect storage

Infrastructure Management Tools (2/16)

• bar_manageMediaServer - BarNC configurations
• bar_manageTeradataSystem - DSMain configurations

Target Group Management Tools (6/16)

• bar_manageDiskFileTargetGroup - Disk file storage solutions
• bar_manageAwsS3TargetGroup - AWS S3 storage solutions
• bar_manageAzureBlobTargetGroup - Azure Blob storage solutions
• bar_manageGoogleCloudTargetGroup - Google Cloud storage solutions
• bar_manageNetBackupTargetGroup - NetBackup storage solutions
• bar_manageIbmSpectrumTargetGroup - IBM Spectrum storage solutions

Operations Management Tools (2/16)

• bar_manageJob - Backup/restore job lifecycle
• bar_manageSaveSets - Backup files/objects management

💼 Business Value

For Database Administrators

• Unified Interface: Single AI-driven interface for all backup operations
• Multi-Cloud Support: Seamless integration across AWS, Azure, Google Cloud
• Enterprise Ready: NetBackup and IBM Spectrum Protect support
• Automated Operations: AI-assisted backup planning and execution

For Organizations

• Cost Optimization: AI-driven storage tier recommendations
• Compliance Ready: Automated backup validation and reporting
• Disaster Recovery: Comprehensive restore capabilities
• Scalability: Support for enterprise-scale backup operations

🔧 Technical Implementation

Core Components

• DSA Client: HTTP API communication layer (✅ Complete)
• Error Handling: Comprehensive error management (✅ Complete)
• Logging: Structured logging throughout (✅ Complete)
• Testing Framework: Automated test validation (✅ Complete)

Implementation Pattern

Each tool follows a consistent pattern with clear naming conventions:

Tool Registration:

• AI Agent sees: bar_[toolName] (e.g., bar_manageDsaDiskFileSystem)
• Internal handler: handle_bar_[toolName] (e.g., handle_bar_manageDsaDiskFileSystem)

Implementation Structure:

def handle_bar_[toolName](operation: str, **kwargs):
    # 1. Input validation
    # 2. DSA API call via dsa_client  
    # 3. Response processing
    # 4. Formatted output
    # 5. Error handling
    
    # Tool metadata registration:
    return {
        "tool_name": "bar_[toolName]",  # ← What AI agent calls
        "content": formatted_response
    }

[dtehan-td]

@Asimz4321 I am trying to understand if this is a Teradata MCP server or a BAR MCP server as you are hitting the DSA API. I guess it could be either. If you would like to talk about submitting something to the repo then let me know, we are always looking for useful modules to add.

[Asimz4321]

Hi @dtehan-td ,

Thank you for your interest! To answer your question - this is definitely intended as an integrated component of the Teradata MCP server, not a separate BAR server.

Purpose:
These tools enable AI-driven Teradata database backup and restore operations across different backup solutions (AWS S3, Azure Blob, Google Cloud, NetBackup, IBM Spectrum, etc.) through DSA integration.

Current Foundation:
I have a working foundation ready in my forked repository:
https://github.com/Asimz4321/teradata-mcp-server/tree/feature/bar-tools-integration/src/teradata_mcp_server/tools/bar

What's Currently Implemented:

• ✅ bar_manageDsaDiskFileSystem tool (fully functional)
• ✅ DSA client integration and error handling
• ✅ Proper MCP tool registration patterns

Request for Review:
Could you please review the current foundation to ensure it aligns with project standards? I'd appreciate confirmation to proceed with implementing the remaining 15 BAR tools, resources, prompts etc.

Plan Forward (pending your approval):

• Complete the remaining 15 BAR tools implementation
• Adhere to project testing guidelines
• Submit a single PR with a squash commit referencing this issue

Looking forward to your feedback!