A standard, open framework for building AI agents is coming from Cisco, LangChain and Galileo

One goal for an agentic future is for AI agents from different organizations to freely and seamlessly talk to one another. But getting to that point requires interoperability, and these agents may have been built with different LLMs, data frameworks and code.

To achieve interoperability, developers of these agents must agree on how they can communicate with each other. This is a challenging task. 

A group of companies, including Cisco, LangChain, LlamaIndex, Galileo and Glean, have now created AGNTCY, an open-source collective with the goal of creating an industry-standard agent interoperability language. AGNTCY aims to make it easy for any AI agent to communicate and exchange data with another.

Uniting AI Agents

“Just like when the cloud and the internet came about and accelerated applications and all social interactions at a global scale, we want to build the Internet of Agents that accelerate all of human work at a global scale,” said Vijoy Pandey, head of Outshift by Cisco, Cisco’s incubation arm, in an interview with VentureBeat. 

Pandey likened AGNTCY to the advent of the Transmission Control Protocol/Internet Protocol (TCP/IP) and the domain name system (DNS), which helped organize the internet and allowed for interconnections between different computer systems. 

“The way we are thinking about this problem is that the original internet allowed for humans and servers and web farms to all come together,” he said. “This is the Internet of Agents, and the only way to do that is to make it open and interoperable.”

Cisco, LangChain and Galileo will act as AGNTCY’s core maintainers, with Glean and LlamaIndex as contributors. However, this structure may change as the collective adds more members. 

Standardizing a fast-moving industry

AI agents cannot be islands. To reach their full potential, they must be able to communicate with other agents that lie outside of an enterprise’s network. This is where interoperability comes in.

Setting standards in traditional industries is challenging enough; it becomes even more difficult for technology like AI, where upgrades and model changes occur every few months. However, this is not the first time a standard has been proposed for generative AI. 

LangChain, one of AGNTCY’s core members, has its own protocol for working with agents built on frameworks other than LangChain. The Agent Protocol, launched in November last year, allows LangChain agents to talk to agents created with AutoGen, CrewAI or any other framework.

Meanwhile, Anthropic announced its Model Context Protocol (MCP) in November. This protocol aims to standardize how models and AI tools connect to data sources. But while many developers have embraced MCP, it’s not exactly a standard just yet. 

Yash Sheth, cofounder of AI evaluation platform Galileo, said standardization “is critical.”

“Standardization is needed, in fact, it will drive increased velocity for agentic adoption. Today, teams are building in silos, having to figure out how to develop their own infrastructure components from scratch,” Sheth said in an email. “Standardization of multi-agentic systems can only happen if these agents powered by non-deterministic models have a strong anchor in measuring and reporting their performance, accuracy and reliability.”

Sheth admits that making AI agents interoperable can be complex. AGNTCY “wants to encourage developers to extend these specs, APIs and tools to suit their needs instead of reinventing the wheel, which will be crucial to achieving standardization.”

LangChain CEO Harrison Chase said in a separate conversation that creating a standard is not impossible, especially now that it’s easier to build the agents themselves. 

“Building agents is already possible, and being done. Replit, Klarna, LinkedIn, Uber, Appfolio and many others have all already done this. Agents aren’t a thing of the future, they are now. Now that we know how to build agents, the next step is to allow them to connect to each other. That is what a standard agent protocol will help enable,” Chase said. 

A platform and a language all at once 

Pandey envisions AGNTCY as more than just a set of codes for agents. It will also allow customers to discover agents from different developers who run the AGNTCY standard. 

“Customers can stitch together all these agents on the AGNTCY platform so they can discover, compose, deploy and evaluate as they build their workflows,” Pandey said.  

AGNTCY still needs to recruit more AI players to add new agents to the platform and gain momentum as a standard. After all, for something to become an industry standard, there needs to be mass adoption, to prevent the establishment of too many competing standards. 

That’s where projects like AGNTCY face an uphill battle. Pandey said the collective has been speaking with many other industry players, and they want to get as many viewpoints as possible while developing the platform. That will take time. 

In the meantime, enterprises continue to experiment and even deploy AI agents. Maybe in the future, these will all be able to speak to each other.