Introducing the Ephemeral Runtime Protocol (ERP): A New Way to Power AI

For a more detailed outline, check out the GitHub Page for ERP

As AI agents become smarter and more autonomous, they’re increasingly being asked to perform complex tasks that require executing temporary code. Whether it’s analyzing data, running simulations, or processing user queries, these tasks often involve dynamic computations that don’t need to persist beyond their immediate use. However, existing frameworks like the Model Context Protocol (MCP) don’t fully address the challenges of securely and efficiently managing these transient execution environments. That’s where the Ephemeral Runtime Protocol (ERP) comes in.

Why Do We Need ERP?

Right now, AI agents are incredibly capable, but they’re limited by how they interact with tools and execute code. MCP has done a fantastic job of standardizing how agents discover and use tools, but it doesn’t handle how or where those tools execute. For example:

What happens when an AI agent needs to run Python code to process a dataset?
How do we ensure that this execution is secure, isolated, and doesn’t hog resources?
How do we make this process seamless across different systems and platforms?

These are the gaps ERP is designed to fill. It provides a framework for creating temporary execution environments —think of them as short-lived sandboxes where code can run safely and efficiently before being discarded. This is critical for tasks like running untrusted code, ensuring resource efficiency, and maintaining security.

How ERP Complements MCP

MCP focuses on tool discovery and context management: it helps AI agents figure out which tools they need and how to use them. ERP picks up where MCP leaves off by handling the actual execution of tasks. Here’s how they work together:

MCP: Finds the right tool for the job (e.g., a Python library or API).
ERP: Creates a secure, temporary environment to execute the task using that tool.

For example, imagine an AI agent tasked with analyzing stock market data:

MCP identifies a financial API and a Python library for data analysis.
ERP spins up a lightweight environment, runs the Python code securely, and then tears it down once the analysis is complete.

By working together, MCP and ERP create a powerful ecosystem where AI agents can not only find the tools they need but also execute them in a safe, efficient way.

Why Make It a Protocol?

ERP isn’t just another piece of software—it’s designed to be an open protocol. Why does that matter? Because protocols are what make systems interoperable, accessible, and future-proof. Here’s why ERP needs to be open, interoperable, and permissionless:

Openness: Anyone should be able to use or contribute to ERP without barriers. This ensures that innovation isn’t locked behind proprietary walls.
Interoperability: AI agents come in all shapes and sizes—some are built on proprietary platforms, while others are open-source. ERP ensures that all these systems can work together seamlessly.
Permissionlessness: Anyone should be able to create an implementation of ERP or use it for their own projects without needing special approval.

By making ERP a protocol rather than a proprietary tool, we’re creating something that can serve as foundational infrastructure for AI systems everywhere—just like HTTP powers the web or SMTP powers email.

How ERP Empowers People to Do More with AI

The beauty of ERP lies in its versatility. Here’s how it can help people unlock new possibilities with AI:

Run Untrusted Code Safely: Imagine you’re using an AI assistant to write custom scripts for your business workflows. With ERP, those scripts can run in isolated environments without risking your system’s security.
Scale Complex Queries: For researchers or developers working on large-scale projects, ERP automates the creation of temporary environments for computationally intensive tasks—no manual setup required.
Collaborative AI Workflows: In multi-agent systems where different AIs specialize in specific tasks (e.g., one generates code while another validates it), ERP ensures smooth handoffs by providing consistent execution environments.

In short, ERP makes it easier for anyone—from developers to businesses—to tap into the full potential of AI without worrying about infrastructure headaches.

The Benefits of an Open Protocol

Here’s why making ERP an open protocol benefits everyone:

Standardization: Just like MCP standardized tool discovery for AI agents, ERP standardizes runtime management. This reduces fragmentation across platforms.
Community-Driven Innovation: An open protocol invites contributions from developers worldwide, leading to faster improvements and broader adoption.
Future-Proofing: By being interoperable and permissionless, ERP ensures compatibility with future technologies and frameworks.

Conclusion

The Ephemeral Runtime Protocol is more than just a technical solution—it’s a step toward making AI more accessible, secure, and capable. By addressing the gaps in runtime management while complementing existing protocols like MCP, ERP empowers developers and users alike to do more with AI.

Whether you’re building cutting-edge AI systems or simply looking for better ways to integrate temporary code execution into your workflows, ERP promises to be a game-changer. And because it’s an open protocol, everyone has a seat at the table—so let’s build this together!