Model Context Protocol AI News & Updates
OpenAI Integrates Third-Party Applications Directly into ChatGPT Interface
OpenAI announced at DevDay 2025 that developers can now build interactive applications that run directly inside ChatGPT, with launch partners including Spotify, Figma, Coursera, Zillow, and Canva. Unlike the previous GPT Store, these apps are embedded within ChatGPT's responses and can be invoked through natural conversation, with OpenAI releasing an Apps SDK for broader developer access. The system uses the Model Context Protocol (MCP) and supports interactive UIs, video rendering, account integration, and future monetization features.
Skynet Chance (+0.01%): Expanding ChatGPT's integration with third-party services and data sources increases the system's reach and potential for unintended interactions across platforms, though this represents primarily a distribution strategy rather than a fundamental capability or alignment concern.
Skynet Date (+0 days): This is an ecosystem and monetization play focused on user experience and developer distribution rather than advancing core AI capabilities or safety mechanisms, resulting in negligible impact on the timeline toward potential AI control scenarios.
AGI Progress (+0.01%): The integration demonstrates progress toward more agentic AI systems that can seamlessly interact with external tools and services, a key component of practical AGI that can take actions across digital environments. However, this is infrastructure and integration work rather than a fundamental capability breakthrough.
AGI Date (+0 days): By creating better tooling and infrastructure for AI-app integration through the Apps SDK and MCP, OpenAI is slightly accelerating the path toward more capable and autonomous AI systems, though the impact is modest as this focuses on existing capabilities rather than new ones.
Google Launches Data Commons MCP Server for AI Training with Real-World Data Access
Google has released the Data Commons Model Context Protocol (MCP) Server, making its vast collection of public datasets accessible to AI systems via natural language queries. This initiative aims to reduce AI hallucinations by providing access to verified, structured data from government surveys, UN statistics, and other authoritative sources. The open standard allows developers to integrate high-quality real-world data into AI training pipelines and applications.
Skynet Chance (-0.03%): Providing AI systems with verified, structured real-world data could slightly reduce risks by making AI outputs more grounded and factual. However, it also enables more powerful AI training, creating a minor mixed impact.
Skynet Date (+0 days): While this improves AI reliability, the focus on data quality and verification suggests a more measured approach to AI development. This emphasis on reducing hallucinations may slightly slow the rush toward potentially unsafe rapid deployment.
AGI Progress (+0.02%): Access to high-quality, structured real-world data represents a meaningful step toward more capable and reliable AI systems. Better training data quality is a key component for advancing toward more general intelligence capabilities.
AGI Date (+0 days): By making vast amounts of structured, verified data easily accessible to AI developers, this could accelerate AI development timelines. The natural language interface and open standard adoption by major companies suggests faster iteration cycles for AI improvements.
Google Adopts Anthropic's Model Context Protocol for AI Data Connectivity
Google has announced it will support Anthropic's Model Context Protocol (MCP) in its Gemini models and SDK, following OpenAI's similar adoption. MCP enables two-way connections between AI models and external data sources, allowing models to access and interact with business tools, software, and content repositories to complete tasks.
Skynet Chance (+0.06%): The widespread adoption of a standard protocol that connects AI models to external data sources and tools increases the potential for AI systems to gain broader access to and control over digital infrastructure, creating more avenues for potential unintended consequences or loss of control.
Skynet Date (-2 days): The rapid industry convergence on a standard for AI model-to-data connectivity will likely accelerate the development of agentic AI systems capable of taking autonomous actions, potentially bringing forward scenarios where AI systems have greater independence from human oversight.
AGI Progress (+0.05%): The adoption of MCP by major AI developers represents significant progress toward AI systems that can seamlessly interact with and operate across diverse data environments and tools, a critical capability for achieving more general AI functionality.
AGI Date (-1 days): The industry's rapid convergence on a standard protocol for AI-data connectivity suggests faster-than-expected progress in creating the infrastructure needed for more capable and autonomous AI systems, potentially accelerating AGI timelines.
OpenAI Adopts Anthropic's Model Context Protocol for Data Integration
OpenAI has announced it will support Anthropic's Model Context Protocol (MCP) across its products, including the ChatGPT desktop app. MCP is an open standard that enables AI models to connect with external data sources and systems, allowing for more relevant and context-aware responses to queries through two-way connections between data sources and AI applications.
Skynet Chance (+0.01%): MCP increases AI systems' ability to access and utilize external data sources, modestly increasing potential autonomy and impact. However, this standardization could also improve oversight by creating more transparent and consistent interfaces between AI systems and external resources.
Skynet Date (-1 days): The adoption of standardized protocols for AI-system integration accelerates the development of more capable AI assistants that can effectively leverage external data and tools. This interoperability milestone removes significant friction in building systems with broader capabilities.
AGI Progress (+0.03%): The adoption of MCP represents meaningful progress toward AGI by enhancing AI systems' ability to interface with diverse data sources and operate effectively across different contexts. This contextual integration capability addresses a key limitation of current AI systems in accessing and utilizing real-time information.
AGI Date (-1 days): Industry convergence on standards like MCP accelerates development by reducing duplicate efforts and enabling faster integration of AI capabilities across applications. The collaboration between competitors on fundamental infrastructure suggests a focus on advancing the field quickly rather than maintaining proprietary advantages.