According to @DeepLearningAI, SAP's Christoph Meyer and Lars Heling detailed at AI Dev 25 x NYC how knowledge graphs improve AI agent discovery and execution by providing semantic and process context to safely invoke the right tools and enterprise APIs, with LLMs supplying fluency and knowledge graphs supplying effectiveness; they covered semantic retrieval, process-aware API connectivity, alignment with the Model Context Protocol (MCP), and ran a demo applying these methods, with the full talk available at piped.video/watch?v=XrYwFUdu2lk; source: @DeepLearningAI on X, Dec 18, 2025. The post does not mention cryptocurrencies, tokens, or market impacts, indicating the session focused on enterprise AI agent reliability rather than crypto-specific use cases; source: @DeepLearningAI on X, Dec 18, 2025.

According to @AnthropicAI, Anthropic is donating the Model Context Protocol (MCP) to the Agentic AI Foundation, a directed fund under the Linux Foundation, to keep MCP open and community-driven. Source: Anthropic on X 2025-12-09 https://twitter.com/AnthropicAI/status/1998437922849350141. According to @AnthropicAI, the company stated MCP has become a foundational protocol for agentic AI in its first year. Source: Anthropic on X 2025-12-09 https://twitter.com/AnthropicAI/status/1998437922849350141. According to @AnthropicAI, the announcement does not mention tokens, blockchain integrations, or financial terms, indicating no direct linkage to crypto assets in this disclosure. Source: Anthropic on X 2025-12-09 https://twitter.com/AnthropicAI/status/1998437922849350141.

According to @AnthropicAI, Anthropic is donating the Model Context Protocol (MCP) and establishing the Agentic AI Foundation, as stated in its announcement titled Donating the Model Context Protocol and establishing the Agentic AI Foundation (source: @AnthropicAI). The announcement describes Anthropic as an AI safety and research company working to build reliable, interpretable, and steerable AI systems (source: @AnthropicAI). The post does not reference cryptocurrencies, tokens, or blockchain, and provides no direct trading catalyst for digital assets based on the source text (source: @AnthropicAI).

According to @AnthropicAI, the Anthropic Engineering blog published guidance on building more efficient agents that handle more tools while using fewer tokens, featuring code execution with the Model Context Protocol (MCP) (source: @AnthropicAI; Anthropic Engineering blog). The post highlights MCP-based code execution for tool-using agents, indicating standardized context management aimed at token efficiency and scalable multi-tool workflows (source: Anthropic Engineering blog; @AnthropicAI). For trading-focused builders, the documented approach can be applied to AI-driven execution and analysis pipelines to integrate more tools while controlling token usage, though the post does not reference cryptocurrencies or market impacts (source: Anthropic Engineering blog; @AnthropicAI).

According to @gdb, ChatGPT now supports the Model Context Protocol (MCP), with the announcement flagged via the official OpenAIDevs post on X. Source: https://twitter.com/gdb/status/1965810388966248652; https://x.com/OpenAIDevs/status/1965807401745207708 The post communicates product support for MCP inside the ChatGPT environment, indicating protocol-level compatibility is being introduced to ChatGPT users and developers. Source: https://twitter.com/gdb/status/1965810388966248652; https://x.com/OpenAIDevs/status/1965807401745207708 No pricing, rollout schedule, or crypto asset references were included in the announcement, so traders should track the OpenAIDevs channel for follow-up technical details before positioning. Source: https://x.com/OpenAIDevs/status/1965807401745207708 For trading relevance, treat this as an AI platform capability headline that can influence near-term sentiment in AI-linked equities and AI-related crypto sectors; monitor volume and liquidity into any official release notes or developer documentation drops. Source: https://x.com/OpenAIDevs/status/1965807401745207708

According to @workspaceupdates, Workspace admins can now build custom deep research connectors using the Model Context Protocol (MCP) in beta, allowing users to integrate proprietary systems and third-party apps for advanced research workflows. This enhanced interoperability is available to Team, Enterprise, and Edu admins, as well as Pro users. The MCP integration is expected to accelerate AI-driven research and knowledge management, directly benefiting AI infrastructure tokens and blockchain projects focusing on enterprise data solutions (source: @workspaceupdates). Crypto traders should monitor projects positioned in enterprise data and AI interoperability, as this update may drive increased demand and innovation in decentralized knowledge management.

According to DeepLearning.AI, the launch of a new course on the Model Context Protocol (MCP) with AnthropicAI aims to standardize integrations between large language models (LLMs) and external tools or data sources, replacing fragmented custom logic (source: DeepLearning.AI Twitter, May 14, 2025). This development streamlines AI workflows, potentially accelerating enterprise adoption and boosting demand for blockchain-based AI solutions. The news is trading-relevant as it may drive renewed interest in crypto AI tokens such as FET, AGIX, and OCEAN, which are positioned to benefit from increased interoperability and enterprise integration in the AI and crypto sectors.

According to Andrew Ng (@AndrewYNg), a new course titled 'MCP: Build Rich-Context AI Apps with Anthropic' has been launched in partnership with Anthropic (@AnthropicAI) and taught by Elie Schoppik (@eschoppik). The course introduces the Model Context Protocol (MCP), enabling developers to build AI applications that efficiently access tools, data, and prompts. This advancement is expected to drive increased adoption of AI-driven blockchain and decentralized app development, potentially influencing related crypto markets as demand for AI-integrated solutions grows (Source: Andrew Ng on Twitter, May 14, 2025).

According to DeepLearning.AI, OpenAI has announced support for the Model Context Protocol (MCP), a standard developed by Anthropic, which facilitates the connection of language models to external tools and proprietary data sources. This integration into OpenAI's Agents SDK is expected to enhance trading algorithms by providing more robust data connectivity and tool compatibility. [Source: DeepLearning.AI](https://twitter.com/DeepLearningAI/status/1913336732948250941)

According to DeepLearning.AI, Andrew Ng emphasizes the importance of starting AI evaluations early and refining them continuously as AI systems evolve. This approach can significantly enhance the performance and reliability of AI models. In the same update, Gemini 2.5 Pro has been noted for leading AI benchmarks, showcasing its superior capabilities. Furthermore, OpenAI's adoption of the Model Context Protocol is set to streamline AI integration processes, while the Byte Latent Transformer emerges as a new innovation in AI architecture. These advancements are crucial for traders looking to leverage AI in algorithmic trading and decision-making processes.