Google Adopts Anthropic's Model Context Protocol for AI Models

Apr 10, 2025
Google has announced its support for Anthropic's Model Context Protocol (MCP) for its Gemini models and SDK, following a similar move by OpenAI.
Google Adopts Anthropic's Model Context Protocol for AI Models

Google has announced its decision to support the Model Context Protocol (MCP) developed by Anthropic for its Gemini models and SDK. This move comes shortly after OpenAI's adoption of the same standard, marking a significant step towards interoperability in AI model data connectivity. The announcement was made by Google DeepMind CEO Demis Hassabis in a post on X.

MCP is designed to enable AI models to access data from various sources, such as business tools and software, facilitating the completion of tasks and enhancing AI applications like chatbots. The protocol allows developers to create two-way connections between data sources and AI-powered applications, improving the integration and functionality of AI systems.

Since its open-source release, MCP has gained traction with companies like Block, Apollo, Replit, Codeium, and Sourcegraph, which have integrated MCP support into their platforms. This widespread adoption underscores the protocol's growing importance in the AI industry as a standard for connecting AI models to data systems.

We hope you enjoyed this article

Consider subscribing to one of our newsletters like Daily AI Brief.

Also, consider following us on social media:

Free newsletter

AI Programming Weekly

Weekly news about AI tools for software engineers, AI enabled IDE's and much more.

Whitepaper

Tensordyne Napier: What If One Rack Could Do the Work of Nine?

Tensordyne

This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.

Read more
Free, six days a week

Daily AI Brief: the AI news that matters, in your inbox.