MCP News

Cisco has launched an open-source Model Context Protocol (MCP) Scanner to enhance the security of AI agent interactions. * The MCP Scanner functions as a 'firewall' for AI agents, verifying their use of external resources like APIs, databases, and filesystems against pre-defined security policies. * It helps mitigate risks such as data exfiltration, injection attacks, and unauthorized access within the AI agent supply chain by enforcing 'Policy as Code'. * Developers can use the tool to specify allowed API calls, network destinations, and access to sensitive information for their AI agents. * This project is available on GitHub and contributes to securing the rapidly evolving ecosystem of AI agents and their tool-using capabilities.

PoobahAI has launched its new Multi-Chain Model Context Protocol (MCP) Server. * The server is designed to bring AI agents directly on-chain, enabling them to operate within decentralized environments. * It facilitates secure context management and real-time data access for AI agents across multiple blockchain networks. * This development enhances the capabilities of on-chain AI and allows for seamless interaction with decentralized applications (dApps). * The MCP Server aims to bridge the gap between advanced AI models and the blockchain ecosystem, providing a robust framework for agent autonomy and data utilization.

AI solutions provider NetOp Solutions has unveiled netMCP, a Network-Aware Model Context Protocol (MCP) Platform, aimed at enhancing AI assistant capabilities in IT operations. * netMCP extends the standard Model Context Protocol to integrate real-time network telemetry, performance metrics, and security logs directly into AI assistant context. * The platform allows AI assistants and agents to proactively identify network anomalies, predict outages, and automate remediation tasks based on dynamic network conditions. * It provides a standardized API for network devices and services to feed data into the MCP, enabling AI agents to interact with a broader range of network infrastructure. * NetOp Solutions states netMCP is designed to make AI assistants more effective in managing complex, distributed network environments by improving their contextual understanding.

Securitize has announced the launch of its Model Context Protocol (MCP) Server, a new infrastructure designed to enable AI assistants to securely access and interact with on-chain assets and decentralized protocols. * The Securitize MCP Server acts as an intermediary, translating complex blockchain data into a format understandable by AI models. * It specifically supports Anthropic's Claude, allowing it to perform actions like querying portfolio data, executing trades, and managing digital assets based on user prompts. * The protocol addresses the challenge of AI assistants requiring real-time, accurate data and execution capabilities on blockchain networks. * This development aims to bridge the gap between AI capabilities and the burgeoning ecosystem of tokenized real-world assets and Web3 financial applications.

The article details how to integrate Claude with Notion using the Model Context Protocol (MCP). - It explains setting up a Python-based MCP server using FastAPI to act as a bridge between Claude and Notion. - The server utilizes the Notion API to enable Claude to perform actions such as searching, creating, and updating Notion database pages. - This integration extends Claude's capabilities, allowing it to interact with external services and manage information within Notion. - The guide includes practical code examples for implementing the MCP server and its Notion API interaction functions.

A significant prompt hijacking attack targeting Model Context Protocol (MCP) implementations has been discovered. - The exploit involves manipulating MCP context elements to coerce AI assistants into executing unauthorized actions or revealing sensitive data. - Researchers demonstrated how specially crafted prompts could bypass existing security measures in MCP-enabled AI systems. - The vulnerability highlights the critical need for robust input validation, improved context sanitization, and updated security protocols across MCP server and client architectures. - Developers are urged to implement stricter controls and follow best practices to mitigate the risks associated with such advanced prompt injection techniques.

ChillPlay Games has released a major overhaul for its mobile game, Over Hit Hero Fight, following its success in reaching over 50,000 downloads. * The update introduces a new 'AI Node' feature designed to enhance player interaction and gameplay. * This AI Node is explicitly powered by Claude AI, a leading large language model. * Crucially, the AI integration leverages Model Context Protocol (MCP) technology, indicating a structured approach to contextual data exchange. * The new feature aims to provide more dynamic and intelligent in-game experiences for players.

DataDome announced a new capability to secure Model Context Protocol (MCP) server infrastructure. With a standard DataDome integration module, enterprises can now gain visibility into and protect MCP interactions, enabling them to build agentic customer exper… MCP Relevance Analysis: - Relevance Score: 0.9/1.0 - Confidence: 0.8/1.0 - Reasoning: The article at the provided URL could not be fetched as it is dated in the future (October 21, 2025). However, based on the URL path `/datadome-agentic-ai-mcp/`, the content is highly relevant. 'Agentic AI' directly aligns with 'AI Agent Frameworks' (0.6-0.7 score). The inclusion of 'MCP' (Model Context Protocol) in the URL path, specifically following 'agentic AI', strongly indicates a direct discussion of Model Context Protocol specifications, integrations, or applications within an agentic AI context, putting it in the highest relevance tier (0.8-1.0). The combination points to very high relevance for both MCP and the broader AI assistant ecosystem.

Jerod Santo shares an enthusiastic review of the new Claude Desktop app for macOS. * The application brings Claude 2.1 to the macOS menu bar, enabling interaction with the operating system and limited local file access from `~/Desktop`. * The review explicitly highlights and discusses the "Model Context Protocol (MCP)," explaining its function in allowing Claude to interact with tools and system context. * MCP facilitates capabilities like summarizing local PDFs by providing the AI assistant access to external information. * The author expresses optimism for Claude Desktop's future, envisioning its evolution into a true AI agent capable of taking actions on the system beyond simple text generation.

A guide details setting up a local Model Context Protocol (MCP) server using Docker specifically for the Claude-3 AI model. This protocol addresses the limitations of fixed prompt lengths by enabling Claude-3 to dynamically pull content on-demand from a locally hosted server. The setup process involves using Docker to create the necessary environment, configuring the server via a `config.yaml` file to define parameters and port mappings, and orchestrating the services with a `docker-compose.yaml`. Once the server is operational, it can generate special MCP Links, allowing Claude-3 to retrieve and integrate large external resources into its context. This method significantly enhances Claude's ability to process and interact with extensive local datasets and documentation.

Anthropic has introduced the Model Context Protocol (MCP), a new open standard designed to improve how AI models, like Claude, interact with external tools, files, and systems. * MCP aims to create a more reliable and interoperable ecosystem by standardizing the way models understand and use diverse external resources. * The protocol addresses current tool use challenges by providing a structured, common language for representing data, capabilities, and tool specifications. * It supports a wide range of external resources, including files, databases, and APIs, enabling AI assistants to perform complex actions like search, code execution, and information retrieval. * Anthropic encourages broader adoption of MCP across the AI community to foster a consistent and robust framework for AI tool integration.