As AI moves beyond chatbots and towards systems that can take actions, the Linux Foundation is launching a new group dedicated to keeping AI agents from splintering into a mess of incompatible, locked-down products.
The group, dubbed the Agentic AI Foundation (AAIF), will act as a neutral home for open-source projects related to AI agents. Anchoring the AAIF at launch are donations from Anthropic, Block, and OpenAI.
Anthropic is donating its MCP (Model Context Protocol), a standard way to connect models and agents to tools and data; Block is contributing Goose, its open-source agent framework; and OpenAI is bringing AGENTS.md to the table, its simple instruction file developers can add to a repository to tell AI coding tools how to behave. You can think of these tools as the basic plumbing of the agent era.
Other members in the AAIF include AWS, Bloomberg, Cloudflare, and Google, signaling an industry-level push for shared guardrails so that AI agents can be trustworthy at scale.
In OpenAI engineer Nick Cooper’s view, protocols are essentially a shared language that lets different agents and systems work together without every developer reinventing integrations from scratch.
“We need multiple [protocols] to negotiate, communicate, and work together to deliver value for people, and that sort of openness and communication is why it’s not ever going to be one provider, one host, one company,” Cooper told TechCrunch.
Jim Zemlin, executive director of the Linux Foundation, put it more bluntly in conversations around the launch: the goal is to avoid a future of “closed wall” proprietary stacks, where tool connections, agent behavior, and orchestration are locked behind a handful of platforms.
“By bringing these projects together under the AAIF, we are now able to coordinate interoperability, safety patterns, and best practices specifically for AI agents,” Zemlin said.
Block – the fintech company behind Square and Cash App – isn’t known for AI infrastructure, but it’s making an openness play with Goose. AI Tech Lead Brad Axen frames it as proof that open alternatives can match proprietary agents at scale, with thousands of engineers using it weekly for coding, data analysis, and documentation.
Open-sourcing Goose serves a dual purpose for Block.
“Getting it out into the world gives us a place for other people to come help us make it better,” Axen told TechCrunch. “We have a lot of contributors from open source, and everything they do to improve it comes back to our company.”
Meanwhile, donating Goose to the Linux Foundation gives Block access to community stress-tests while positioning it as a working example of AAIF’s vision – an agent framework designed to plug into shared building blocks like MCP and AGENTS.md.
Anthropic is making a similar move at the protocol layer, handing MCP to the Linux Foundation. The goal: make MCP the neutral infrastructure connecting AI models to tools, data, and applications without endless one-off adapters.
“The main goal is to have enough adoption in the world that it’s the de facto standard,” MCP co-creator David Soria Parra told TechCrunch. “We’re all better off if we have an open integration center where you can build something once as a developer and use it across any client.”
Donating MCP to AAIF signals that the protocol won’t be controlled by a single vendor.
That governance point is central to why the Linux Foundation created a new umbrella at all. The organization already hosts major AI and developer infrastructure projects – everything from PyTorch and Ray to Kubernetes – but says AAIF is specifically aimed at agent standards and orchestration, including shared safety patterns and interoperability.
AAIF’s structure is funded through a “directed fund,” meaning companies can contribute money through membership dues. But Zemlin of the Linux Foundation argues that funding doesn’t equal control: project roadmaps are set by technical steering committees, and no single member gets unilateral say over direction.
Still, the big question is whether AAIF becomes real infrastructure or just another industry logo alliance.
“An early indicator of success, in addition to adoption of these standards, would be the development and implementation of shared standards being used by vendor agents around the world,” Zemlin said.
For OpenAI’s Cooper, success would look like an evolution of standards: “I don’t want it to be a stagnant thing. I don’t want these protocols to be part of this foundation, and that’s where they sat for two years. They should evolve and continually accept further input.”
There’s also a more subtle consequence: even with open governance, one company’s implementation could become the default simply because it ships fastest or gains the most usage. Zemlin says that’s not necessarily a bad thing, though. He points to open-source history – like Kubernetes “winning” the container race – as evidence that “dominance emerges from merit and not vendor control.”
For developers and enterprises, the short-term appeal is clear: less time building custom connectors, more predictable agent behavior across codebases, and simpler deployment in security-conscious environments.
The larger vision is more ambitious: if tools like MCP, AGENTS.md, and Goose become standard infrastructure, the agent landscape could shift from closed platforms to an open, mix-and-match software world reminiscent of the interoperable systems that built the modern web.
