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Anush DSouza

Senior Product Manager at Heroku
Heroku Staff

Anush is a Senior Product Manager at Heroku with a Focus on Front End and Developer tools.

Building Data-Aware AI Applications with Heroku AI and LlamaIndex

Building AI applications that can interact with private data is a common goal for many organizations. The challenge often lies in connecting large language models (LLMs) with proprietary datasets. A combination of Heroku Managed Inference and Agents and LlamaIndex provides an elegant stack for this purpose.

This post explores how to use these tools to build retrieval-augmented generation (RAG) applications. We’ll cover the technical components, Use Cases and the development process, and how to get started.

Building Agents With Heroku AI and Pydantic AI

Building production-grade AI applications can be complex, but with Heroku and Pydantic AI, developers gain a powerful and reliable solution for integrating advanced AI capabilities. Heroku makes it easy to integrate AI into your applications with Heroku Managed Inference and Agents. With a single click, you can attach powerful Large Language Models like Anthropic’s Claude 4 Sonnet to your apps. Heroku AI also provides built-in tools like secure code execution and an OpenAI-compatible API that you can drop directly into popular frameworks and SDKs.

Heroku AI: Heroku Remote MCP Server

Today, we’re thrilled to announce a new way in which agents can access the Heroku platform using the Heroku Remote MCP Server, now available at https://mcp.heroku.com/mcp.

This new remote server is an expansion of our earlier stdio-based MCP server and comes with secure OAuth authentication. It’s designed to provide a secure, scalable, and incredibly simple way for agents to interact with the Heroku platform and use tools to perform actions such as creating a Heroku …

Heroku AI: Claude 4 Sonnet is now available

Anthropic’s Claude 4 Sonnet, part of the next generation of Claude models, is now available on Heroku Managed Inference and Agents. This gives developers immediate access to a model designed for coding, advanced reasoning, and the support of capable AI agents. Heroku Managed Inference and Agents expands your AI choices, offering the freedom to build transformative applications with the developer and operational ease Heroku is known for. Claude 4 Sonnet extends what’s possible with …

Heroku AI: Managed Inference and Agents is now Generally Available

Many of the most exciting experiences we’re beginning to rely on every day are powered by AI; whether it’s conversational assistants, personalized recommendations or code generation, these experiences are powered by inference systems and intelligent agents. Behind the scenes, developers offload complex decisions, automate tasks, and compose intelligent applications using large language models and tool execution flows. Together, these AI-powered primitives are becoming a key complement to traditional application development, enabling a new wave of …

Heroku AI: Build and Deploy Enterprise Grade MCP Servers

Agents hold immense power, but their true potential shines when they connect to the real world, fetching data, triggering actions, or leveraging external tools. The Model Context Protocol (MCP) offers a standardized way for AI agents to do this.

MCP is an open protocol that standardizes how applications provide context to LLMs. Think of MCP like a USB-C port for AI applications. Just as USB-C provides a standardized way to connect your devices to various …

Introducing Heroku-Streamlit: Seamless Data Visualization

We’re excited to announce the release of Heroku-Streamlit, a template that makes deploying interactive data visualization applications on Heroku simpler than ever before. Streamlit is an open-source app framework built for machine learning and data science projects. This Streamlit App brings together Heroku’s scalable cloud platform and Streamlit’s intuitive Python-based data application framework. Whether you’re a data scientist, educator, or developer, you can now spin up a cloud-based Streamlit environment in minutes.

What is Heroku-Streamlit?

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Introducing the Official Heroku MCP Server

We’re excited to announce the launch of the Heroku MCP Server, designed to bridge the gap between agent-driven development and Heroku’s AI PaaS. Having defined the platform experience for apps in the cloud, Heroku extends our developer and operator experience to AI capabilities. With the Heroku MCP Server, you can now expose Heroku’s robust platform capabilities as a set of intuitive actions accessible to AI agents through Model Context Protocol (MCP).

The Heroku MCP server enables AI-powered applications like Claude Desktop, Cursor, and Windsurf to directly interface with Heroku, unlocking new levels of automation, efficiency, and intelligence for managing your custom applications.

Jupyter Notebooks on Heroku with Persistent Storage

We’re excited to introduce Heroku-Jupyter, an open-source, production-ready solution for running Jupyter Notebooks on Heroku with persistent storage, seamless deployment, and built-in security. Whether you’re a data scientist, educator, or developer, you can now spin up a cloud-based Jupyter environment in minutes.

Heroku Extension for Visual Studio Code (VS Code) Now Generally Available

The Heroku Extension for Visual Studio Code (VS Code) is now generally available for all customers—VS Code is an all-in-one tool that brings Heroku’s cloud management directly to your favorite IDE. In today’s fast-paced, AI-assisted development environment, switching between code editors and deployment tools can slow innovation and product delivery. ‌This extension lets you focus on building great applications by streamlining cloud resource monitoring, one-click deployments, and add-on management, all within VS Code.

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