MLOps Workshop: Structured Data For Agents - Bringing MCP to the Enterprise

Structured Data For Agents: Bringing MCP to the Enterprise

Unlock the power of structured data for enterprise-grade intelligent agents! Join Simba Khadder from Featureform on May 1st to discover how enterprises can enhance their MCP implementations alongside Featureform and Apache Iceberg to operationalize structured data effectively. Learn how innovative technologies build upon MCP, enabling seamless integration and standardized interactions between intelligent agents and your existing data infrastructure. Gain practical insights and explore real-world examples showcasing this powerful synergy.

Highlights:

• Advanced MCP implementation strategies
• Operationalizing structured data for enterprise agents
• Real-time and batch pipeline integration using Apache Iceberg
• Real-world enterprise use cases with Featureform

Towards the end of the session, there will be time for Q&A.

What is Featureform:

Featureform is a virtual feature store that enables data scientists to define, manage, and serve their ML model's features. It sits atop existing infrastructure, transforming it into a traditional feature store. Using Featureform, data science teams can enhance collaboration, organize experimentation, facilitate deployment, increase reliability, and ensure compliance. It allows standardized definitions of transformations, features, labels, and training sets, making them easily shareable and understandable across teams. Additionally, Featureform is designed to work with individual data scientists and large enterprise teams, providing a centralized repository for machine learning resources.

Check out our open-source Feature Store here:

https://github.com/featureform/featureform

What is MCPEngine

To unlock MCP’s full potential for real-world applications, Featureform released MCPEngine, an open-source (MIT-licensed) project designed to bring security, scalability, and modern API practices to the MCP ecosystem.

MCPEngine is composed of two parts:

MCPEngine-Proxy — a lightweight Go-based proxy that bridges the gap between MCP’s stdio and HTTP-SSE transports. It introduces proper authentication via OAuth in a way that is custom but compliant with spec. When an LLM like Claude hits a protected resource, we return a standard HTTP 401 Unauthorized and initiate a familiar OAuth flow. Claude (or any other client) simply prints a login link. The proxy handles the rest transparently, without requiring any custom logic from hosts like Claude for Desktop.

MCPEngine — a fully-featured, backward-compatible MCP server framework. It extends the official MCP SDK by embedding authentication and authorization natively, allowing you to expose secure MCP-compatible endpoints without resorting to hacks, workarounds, or local-only implementations.

Check out MCPEngine here:
https://github.com/featureform/mcp-engine