Empowering Agentic AI with IBM Storage Insights: Introducing Our Open Source MCP Server
By Binayak Dutta, Lead AI Architect and Data Scientist, IBM Storage Insights
Today marks a significant milestone in our journey toward intelligent storage management as we announce the open source release of the IBM Storage Insights Model Context Protocol (MCP) Server. This release represents our commitment to democratizing AI-powered storage observability and enabling seamless integration with the rapidly evolving Agentic-AI ecosystem.
Bridging AI and Storage Intelligence
IBM Storage Insights has established itself as a leading AI-powered observability platform specifically designed for IBM Storage Systems. Our platform continuously monitors, analyzes, and provides actionable insights for enterprise storage environments, helping organizations optimize performance, predict issues, and maintain peak operational efficiency.
With the growing adoption of AI agents and conversational interfaces in enterprise workflows, we recognized the need to make our powerful storage intelligence accessible through modern AI frameworks. The MCP Server bridges this gap, allowing organizations to integrate Storage Insights capabilities directly into their AI-powered workflows and decision-making processes.
Technical Foundation: Built for Modern AI Ecosystems
Our MCP Server is developed using Python's FastMCP library, ensuring robust performance and seamless integration with various AI platforms. The server acts as a sophisticated intermediary that leverages IBM Storage Insights' comprehensive REST APIs, making our observability capabilities accessible to any MCP-compatible AI system.
The architecture is designed with simplicity and security in mind. Customers who have registered with IBM Storage Insights can easily configure the MCP Server using their existing Tenant ID and API Key credentials. This approach ensures that organizations can quickly deploy the solution without complex authentication workflows while maintaining enterprise-grade security standards
Comprehensive Storage Observability Through AI
The MCP Server surfaces critical Storage Insights APIs that provide deep visibility into IBM Flash System Storage and IBM DS8K Storage environments. Through natural language interactions with AI agents, storage administrators and IT professionals can now:
- Monitor real-time performance metrics and capacity utilization
- Receive proactive alerts and notifications about potential issues
- Analyze historical trends and performance patterns
- Diagnose storage problems through conversational interfaces
- Access detailed system configurations and component status
This capability transforms how organizations interact with their storage infrastructure, moving from traditional dashboard-based monitoring to intuitive, conversational intelligence that can be embedded into existing workflows.
Enabling the Agentic AI Revolution
The release of our MCP Server represents a crucial step toward enabling truly Agentic-AI solutions in enterprise storage management. By integrating with AI assistants and agents, organizations can create sophisticated automation workflows that combine storage intelligence with broader IT operations.
Imagine an AI agent that can automatically correlate storage performance anomalies with application issues, recommend optimization strategies based on historical patterns, or proactively schedule maintenance activities based on predictive analytics. These scenarios become reality when Storage Insights intelligence is accessible through natural language interfaces powered by large language models.
Proven Integration and Testing
We've tested our MCP Server across multiple AI platforms to ensure broad compatibility and reliable performance:
Our integration with the MCP Inspector provides developers and system administrators with a comprehensive testing environment for validating MCP Server functionality and exploring available storage insights capabilities.
- Claude Desktop with Claude Sonnet 4
We've validated seamless integration with Anthropic's Claude Desktop, leveraging the powerful Claude Sonnet 4 LLM for sophisticated storage analysis and recommendations. This combination delivers enterprise-grade conversational AI capabilities with deep storage domain expertise.
Illustrations with Claude Desktop with Claude Sonnet 4
Tool Listing after registering MCP Server
Elaborating tool Capabilities
Listing Capacity Metrics for selected Storage system
- IBM Watsonx Orchestrate Desktop with Granite 3 8B Instruct
Integration with IBM's own Watsonx Orchestrate Desktop, powered by the Granite 3 8B Instruct model, demonstrates our commitment to supporting IBM's broader AI ecosystem while providing customers with enterprise-ready solutions built on IBM's trusted AI foundation.
Illustration with Watsonx Orchestrate with Granite 3-8b Instruct Model
Tool Listing after registering MCP Server
Fetch IO Rate for selected Tenant ID and System ID
Open Source: Fostering Innovation and Collaboration
By open sourcing our MCP Server, we're inviting the global developer community to contribute, extend, and build upon our work. We believe that the future of enterprise AI lies in collaborative development and shared innovation.
The source code, documentation, and examples are available on GitHub:
https://github.com/IBM/ibm-storageinsights-mcpserver
We encourage developers, storage professionals, and AI enthusiasts to explore the codebase, submit issues, contribute enhancements, and share their innovative use cases with the community.
The Beginning of Our Agentic AI Journey
This open source release of the IBM Storage Insights MCP Server represents just the first step in our broader agentic AI journey. We envision a future where AI agents seamlessly orchestrate complex storage operations, predict and prevent issues before they impact business operations, and provide intelligent recommendations that continuously optimize storage environments.
Our roadmap includes expanding API coverage, developing specialized AI agents for specific storage use cases, and integrating with emerging AI frameworks and platforms. We're committed to staying at the forefront of the intersection between AI and storage technology.
Getting Started
For IBM Storage Insights customers interested in exploring the MCP Server, detailed documentation and setup guides are available in our GitHub repository. The integration process is designed to be straightforward, requiring only your existing Storage Insights credentials and a compatible AI platform.
We're excited to see how the community will leverage this capability to create innovative solutions that transform storage management through the power of Agentic-AI.
References:
- Please use this Github repo link to access the open source project in Git hub repository
- For details on IBM Storage Insights, please refer our product page https://www.ibm.com/products/storage-insights
- For a hands-on experience with IBM Storage Insights, please use our demonstration link https://demo.insights.ibm.com/
- For a quick summary of recent features released with IBM Storage Insights, please refer https://www.ibm.com/docs/en/storage-insights?topic=whats-new
Thank you.
Binayak Dutta
AI-Architect & Lead Data Scientist
IBM Storage Insights
For questions, support, or to share your experiences with the IBM Storage Insights MCP Server, please reach out through our GitHub repository or IBM Storage Insights support channels.