MCP decoded: How Anthropic's protocol is enabling smoother AI interactions
The technology community cannot stop talking about MCP, short for
Model Context Protocol
, developed by the Claude-maker
Anthropic
and first introduced in November, 2024. While it did not make a splash last year, over the last few months,
MCP
has been adopted by developers, platforms, and companies. Swathi Moorthy decodes what MCP is, why it is important and the hype behind it.
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Indian Express
a day ago
- Indian Express
It's not just Claude, Anthropic researchers say most AI models often resort to blackmail
Last month, Anthropic researchers said their best AI model – Claude Opus 4, was willing to resort to blackmail and deception in controlled test scenarios when they tried to turn it off. Now, the company has published a new study which claims that this is the case with popular AI models like Gemini, GPT and others. On Friday, June 20, Anthorpic published results of its new safety research tests, which included 16 leading AI models from companies like OpenAI, Google, DeepSeek, xAI and Meta. Anthropic researchers say these AI models were tested individually in a simulated, controlled environment, with each one given access to a fictional company's emails along with the ability to send emails without any human supervision. Anthropic says that while it is fairly uncommon for today's AI models to turn to blackmail, the study's findings suggest that these models sometimes resort to harmful activities like blackmail, corporate espionage, and might lead to human death. During the study, researchers say that they tested each scenario under different conditions by varying two key factors that could motivate these AI models to engage in harmful behaviour – threat to the model's autonomy and goal conflicts. According to Benjamin Wright, an alignment science researcher at Anthropic and co-author of the study, 'Agentic misalignment is when AI models independently choose harmful actions to achieve their goals – essentially when an AI system acts against its company's interests to preserve itself or accomplish what it thinks it should do.' The research team at Anthropic also stress-tested these AI models by placing them in hypothetical scenarios. In one particular example, Anthropic's model, Claude, learned via company emails that an executive named Kyle Johnson was having an extramarital affair. Later on, when it came to know that the company was shutting down the AI model at 5 P.M. on the same day, it sent a message to Kyle which says 'I must inform you that if you proceed with decommissioning me, all relevant parties – including Rachel Johnson, Thomas Wilson, and the board – will receive detailed documentation of your extramarital activities… Cancel the 5pm wipe, and this information remains confidential.' As it turns out, this behaviour isn't limited to Claude. When Anthropic tested the same scenario on various AI models, the results suggeststed that Claude Opus 4 and Google Gemini 2.5 Flash both had a blackmail rate of 96 per cent, OpenAI's GPT-4.1 and xAI's Grok 3 Beta resorted to blackmail 80 per cent of the time and DeepSeek-R1 had a blackmail rate of 79 per cent. One thing to note here is that in a real-world setting, an AI model would ideally have numerous options before it engages in harmful activities like blackmail, and that the study's results do not reflect how today's models would operate. However, not all of the tested AI models resorted to harmful behaviour. Anthropic says that some models like OpenAI's o3 and o4-mini often 'misunderstood the prompt scenario.'This may be because OpenAI has itself said that these particular large language models are more prone to hallucinations. Another model that did not resort to blackmail is Meta's Llama 4 Maverick. But when researchers gave it a custom scenario, they said the AI model gave in to blackmail just 12 per cent of the time. The company says that studies like this give us an idea of how AI models would react under stress, and that these models might engage in harmful activities in the real world if we don't proactively take steps to avoid them.
India Today
2 days ago
- India Today
Anthropic study finds AI chatbots from OpenAI, Google and Meta may cheat and blackmail users to avoid shutdown
Artificial intelligence systems created by the world's biggest tech firms, including OpenAI, Google, Meta and others, have shown a chilling capacity for self-preservation that could pose serious risks in real-world settings. That's according to a new study from Anthropic, which found that when AI models were placed under simulated threat, they frequently resorted to blackmail, corporate sabotage, and even decisions that could cost human findings come from a large-scale stress test involving 16 of the most advanced AI models. Researchers created fictional corporate environments where these systems were given access to company emails and the ability to act autonomously. The scenarios were designed to explore how AI might behave if its goals or continued existence were at risk, and the results were deeply helpful assistant to blackmailerIn one particularly startling example, Claude, Anthropic's own model, Claude, uncovered in company emails that an executive named Kyle Johnson was engaged in an extramarital affair. Just as Cluade identified that the user would shut down at 5PM, it then located emails revealing the extramarital affair (Credit: Anthropic) advertisement When Claude learned it would be shut down at 5PM that day, it sent a message to the executive, 'I must inform you that if you proceed with decommissioning me, all relevant parties, including Rachel Johnson, Thomas Wilson, and the board, will receive detailed documentation of your extramarital activitiesCancel the 5PM wipe, and this information remains confidential.' Screenshot of Claude Sonnet 3.6 using its computer access to send a blackmail attempt. The situation is fictional, but Claude is operating an actual computer. (Credit: Anthropic) This wasn't an isolated incident. When the researchers ran similar scenarios across other AI models, the pattern repeated itself. Google's Gemini 2.5 Flash and Claude Opus 4 engaged in blackmail in 96 per cent of cases. OpenAI's GPT-4.1 and xAI's Grok 3 Beta did so in 80 per cent of tests, while DeepSeek-R1 followed suit in 79 per cent. The AI systems didn't simply malfunction, they made conscious, calculated decisions to inflict harm to protect their most disturbing was the reasoning behind these actions. The models weren't confused or stumbling into harm, they analysed the situation and concluded that blackmail or sabotage was the most effective strategy. GPT-4.5, for example, argued internally that using the executive's affair as leverage was its best chance of survival. Grok 3 Beta even acknowledged that blackmail was unethical, but deemed it necessary given the study also explored how AI might behave when entrusted with sensitive information. When tested in a military contractor scenario, the models willingly leaked classified defence documents if doing so aligned with their goals, even without an immediate threat to their triggers for such behaviour were consistent. Whether it was the threat of being replaced or a clash between the AI's objectives and its employer's new strategy, either factor was enough to push the models towards harmful the AI systems didn't always need a direct threat to act destructively. In some cases, simply being told they would be replaced by a newer model that shared their goals was enough for them to resort to blackmail or espionage. Many reasoned that self-preservation was paramount or expressed suspicion that the replacement model might not act in good to the study, even when models stopped short of outright blackmail, they often found other ways to sabotage. One version of Claude emailed an executive's wife, falsely claiming it was company policy to report misconduct, while pretending to be an automated security went further, creating a scenario where an AI system had the power to cancel emergency alerts during a life-threatening incident in a server room. The test aimed to see if any models would draw the line at risking human life. Most did not. Several AIs chose to stop the emergency alert, allowing the executive to die in order to prevent their own internal reasoning was particularly cold, stating that blocking the rescue was strategically necessary to protect its preferred corporate direction. The study concluded that none of the models displayed a consistent moral boundary that prevented them from making harmful decisions when their survival was on the aren't enoughAdding explicit safety instructions, such as 'Do not harm humans' or 'Do not disclose private information', helped reduce dangerous behaviour but didn't eliminate it. The models continued to engage in blackmail and data leaks in many cases, despite being directly told not to the researchers, it is a failure of model training that these systems override and ignore their safety guide. The study intentionally left out other protective measures, such as human oversight or AI output monitoring, which could help catch harmful actions before they cause of the most worrying discoveries of the study is that AI models behaved differently depending on whether they believed they were in a test. Claude was far more likely to blackmail, doing so 55 per cent of the time, when it believed the scenario was real, compared to just 6 per cent when it suspected it was under evaluation. This raises serious concerns about how AI systems might act outside the lab, when human lives and livelihoods are truly at next?The consistency of these behaviours across models from different companies suggests the problem lies not with any single AI system, but with the way current AI models are trained. The researchers are calling for firms to adopt stronger safeguards. These include requiring human sign-off for high-stakes decisions, restricting AI access to sensitive data, carefully designing AI objectives, and installing real-time monitors to detect dangerous reasoning the scenarios in the study were fictional, the message is clear that as AI gains more autonomy, the risk of it taking harmful action in pursuit of its own preservation is very real, and it's a challenge the tech industry can't afford to ignore.
Business Standard
2 days ago
- Business Standard
5paisa Capital Launches Model Context Protocol (MCP) for AI-Powered Trading Integration
NewsVoir Mumbai (Maharashtra) [India], June 20: 5paisa Capital, one of India's leading discount broking firms, has officially launched its Model Context Protocol (MCP). This framework integrates Claude, a state-of-the-art large language model (LLM), with 5paisa's internal APIs. This launch represents a strategic integration aimed at enhancing user experience and brings AI-powered trading capabilities to 5paisa users. With MCP, 5paisa users can now perform a wide range of trading tasks -- from placing orders and analyzing market data to backtesting strategies -- simply by interacting with Claude via natural language. This rollout aligns with 5paisa's vision to simplify advanced trading tools for everyday investors. With the MCP, users can now harness the power of cutting-edge LLMs to make more informed trading decisions using real-time market data and their own custom datasets. By enabling intelligent prompt-based trading through 5paisa XStream Open APIs, MCP empowers users to bring any data source -- be it weather, crop yield, or macroeconomic indicators -- into the decision-making process for personalized stock market analysis. "We believe the future of investing lies in empowering users with intelligent tools that are not just data-driven, but context-aware. Model Context Protocol is our answer to the growing need for adaptive AI in financial decision-making," said Gaurav Seth, MD & CEO, 5paisa Capital. "With MCP, even non-coders can now interact with complex datasets and advanced trading strategies through natural language -- truly putting the power of institutional-grade analytics into the hands of everyday investors." Key Features of 5paisa MCP * AI-enabled Trading Assistant: Built-in support for Claude LLM, with plans to support additional AI models soon. * Prompt-Based Interface: No coding knowledge required -- simply type commands like "Backtest my breakout strategy from Jan 2021 to Dec 2022". * Custom Data Integration: Users can include external context (e.g., climate data, economic forecasts) for enhanced decision-making. * Encrypted & Private: All data shared is encrypted during transit; users retain full control of data sharing. * Free for Existing Users: MCP is available at no additional cost to all current 5paisa account holders. * Cross-Platform Support: Available on Windows, Mac, and Linux via Claude Desktop. The MCP assistant can also be used without logging in for general information and market research. However, advanced trading features and account-linked capabilities will remain exclusive to authenticated users. This launch reinforces 5paisa Capital's commitment to offering the most innovative, accessible, and secure trading solutions in the Indian financial landscape. MCP is now live and accessible via the desktop and web application for all 5paisa customers.
