Google joins OpenAI in adopting Anthropics protocol for connecting AI agents why it matters
Weeks earlier, OpenAI embraced the Model Context Protocol. Finally, AI rivals are cooperating on something.
Three major AI companies—Google, OpenAI, and Anthropic—have found common ground by adopting Anthropic's Model Context Protocol (MCP), a standard designed to improve how AI systems access data and applications. This rare collaboration among typically competitive firms signals a shift toward interoperability in the AI industry.
Key Developments
- Google announced via an X post that it will support MCP for its Gemini models and SDK, joining OpenAI, which committed to MCP in March.
- MCP (Anthropic’s open-source protocol) simplifies integration for AI agents by providing a unified standard to access data stores, developer tools, and enterprise applications.
- Other adopters include Block, Apollo, and Replit, suggesting broader industry momentum.
Why It Matters
AI agents—autonomous assistants that perform tasks—are only as effective as their access to data. Currently, integrating agents with enterprise systems requires custom work for each data source, which is time-consuming and hard to scale. MCP streamlines this by offering pre-built servers for platforms like Google Drive, GitHub, and Slack.
Industry Reactions
- Demis Hassabis, CEO of Google DeepMind, called MCP "a good protocol" and praised its potential as an open standard for the "AI agentic era."
- OpenAI plans to extend MCP support to ChatGPT on desktop and mobile, though no timeline was provided.
Broader Implications
The adoption of MCP reflects a growing trend toward open-source collaboration in AI, particularly for enterprise applications. As AI agents become more advanced, standardized protocols like MCP could accelerate adoption and interoperability across industries.
For more on AI agents, read What are AI agents?.
Editorial Note: Google has not yet specified a rollout timeline for MCP support.
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About the Author

Dr. Emily Wang
AI Product Strategy Expert
Former Google AI Product Manager with 10 years of experience in AI product development and strategy formulation. Led multiple successful AI products from 0 to 1 development process, now provides product strategy consulting for AI startups while writing AI product analysis articles for various tech media outlets.