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Anthropic Donates Model Context Protocol to Linux Foundation, Co-founds Agentic AI Foundation
Anthropic is donating the Model Context Protocol (MCP) to the newly established Agentic AI Foundation (AAIF), a directed fund under the Linux Foundation co-founded by Anthropic, Block, and OpenAI, with support from Google, Microsoft, AWS, Cloudflare, and Bloomberg. MCP has reached significant adoption milestones including 10,000+ active public servers, 97M+ monthly SDK downloads, and integration into ChatGPT, Gemini, Microsoft Copilot, and Visual Studio Code. The AAIF will also house Block's goose and OpenAI's AGENTS.md as founding projects, aiming to foster open, vendor-neutral standards for agentic AI. MCP governance will remain community-driven with existing maintainers continuing their roles.
OpenAI co-founds Agentic AI Foundation, donates AGENTS.md
OpenAI has co-founded the Agentic AI Foundation, a new organization housed under the Linux Foundation, aimed at developing open and interoperable standards for safe agentic AI systems. As part of this initiative, OpenAI is donating AGENTS.md, a specification document, to the foundation. The move signals OpenAI's intent to shape industry-wide norms around agentic AI through open governance structures rather than proprietary control.
Taxonomy and governance gap analysis for AI contributors in open-source software
A preprint from arXiv analyzes how open-source organizations are handling AI-generated and agent-driven contributions, comparing policies across six major projects (SymPy, LLVM, matplotlib, OpenInfra, Apache Software Foundation, Linux Foundation). The authors develop a six-dimensional taxonomy covering disclosure, responsibility, human oversight, licensing, enforcement, and maintainer workload, and score each organization's policy maturity. The paper maps documented agent incidents onto governance gaps and identifies misalignments with emerging regulatory frameworks including the EU AI Act, NIST AI RMF, and ISO/IEC 42001, proposing a harmonized tiered framework.
Claude Mythos Preview: Limited-Release Frontier Model with Exceptional Cybersecurity Capabilities
Anthropic has published a 244-page model card for Claude Mythos Preview, a frontier model not yet commercially available, which autonomously discovered thousands of high-severity vulnerabilities in popular operating systems and browsers during testing. To mitigate risks before potential deployment, Anthropic assembled Project Glasswing, a consortium of over 40 organizations including AWS, Apple, Google, Microsoft, and CrowdStrike, funded with $100M in model credits to patch vulnerabilities proactively. The model substantially outperforms Claude Opus 4.6, GPT-5.4, and Gemini 3.1 Pro across multiple benchmarks including CyberGym (83.1%), Terminal-Bench 2.0 (82%), GPQA Diamond (94.5%), HLE (64.7%), and GraphWalks long-context (80%). The Batch notes parallels to OpenAI's GPT-2 limited-release strategy and characterizes the announcement as having elements of a publicity stunt alongside genuine safety concerns.
Anthropic Releases Claude Mythos Preview with Extraordinary Cybersecurity Capabilities, Forms Project Glasswing Consortium
Anthropic has published a 244-page model card for Claude Mythos Preview, a large language model not yet commercially available, which broadly outperforms Claude Opus 4.6 and is described as 'strikingly capable' at identifying and exploiting code vulnerabilities. To mitigate risks before potential release, Anthropic assembled Project Glasswing, a consortium including AWS, Apple, Google, Microsoft, CrowdStrike, Nvidia, and 40+ other organizations, funded with $100 million in API credits and $4 million in open-source security donations. This marks the first time Anthropic has published a model card without making the model commercially available, signaling an unusual safety-first deployment posture. The issue also includes commentary from Andrew Ng on AI's impact on software engineering jobs, arguing against an 'AI jobpocalypse' narrative.
MLflow trending on GitHub as open-source AI engineering platform
MLflow, an open-source platform for managing AI/ML workflows, is trending on GitHub with 26,442 total stars and 22 new stars today. The project supports agents, LLMs, and traditional ML models, offering debugging, evaluation, monitoring, and optimization capabilities for production AI applications. It is a mature, widely-used tooling platform in the MLOps space.