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.
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