在5G与数字生态融合背景下,GSMA Open Gateway通过标准化API与统一接入框架,实现应用在全球运营商网络的可移植与规模化部署,降低开发与适配成本,推动运营商能力开放。然而,跨运营商能力调用仍是关键瓶颈。因此,梳理了CAMARA 4类应用程...在5G与数字生态融合背景下,GSMA Open Gateway通过标准化API与统一接入框架,实现应用在全球运营商网络的可移植与规模化部署,降低开发与适配成本,推动运营商能力开放。然而,跨运营商能力调用仍是关键瓶颈。因此,梳理了CAMARA 4类应用程序编程接口(API)分发模式,对比分析了国内外实践差异。其中,国内运营商针对国内5G网络按需质量保障(QoD)3网互通中聚合平台(Aggregator)面临的痛点,提出了以软件开发工具包(SDK)为核心的解决方案。这一方案通过了统一认证和中国香港商用案例的可行性验证。此外,我国还提出了“SDK+Open Gateway”全球推广与模型上下文协议(MCP)模式演进路径,为全球运营商跨网协同提供中国经验,推动生态从技术框架迈向规模商用,助力数字经济高质量发展。展开更多
Density-functional-theory(DFT)simulations with the Vienna Ab initio Simulation Package(VASP)are indispensable in computational materials science but often require extensive manual setup,monitoring,and postprocessing.H...Density-functional-theory(DFT)simulations with the Vienna Ab initio Simulation Package(VASP)are indispensable in computational materials science but often require extensive manual setup,monitoring,and postprocessing.Here,we introduce VASPilot,an open-source platform that fully automates VASP workflows via a multi-agent architecture built on the CrewAI framework and a standardized model context protocol(MCP).VASPilot’s agent suite handles every stage of a VASP study from retrieving crystal structures and generating input files to submitting Slurm jobs,parsing error messages,and dynamically adjusting parameters for seamless restarts.A lightweight Quart-based web interface provides intuitive task submission,real-time progress tracking,and drill-down access to execution logs,structure visualizations,and plots.We validated VASPilot on both routine and advanced benchmarks:automated band-structure and density-of-states calculations(including on-the-fly symmetry corrections),plane-wave cutoff convergence tests,lattice-constant optimizations with various van der Waals corrections,and cross-material band-gap comparisons for transition-metal dichalcogenides.In all cases,VASPilot completed the missions reliably and without manual intervention.Moreover,its modular design allows easy extension to other DFT codes simply by deploying the appropriate MCP server.By offloading technical overhead,VASPilot enables researchers to focus on scientific discovery and accelerates high-throughput computational materials research.展开更多
With the widespread deployment of large language models(LLMs)in complex and multimodal scenarios,there is a growing demand for secure and standardized integration of external tools and data sources.The Model Context P...With the widespread deployment of large language models(LLMs)in complex and multimodal scenarios,there is a growing demand for secure and standardized integration of external tools and data sources.The Model Context Protocol(MCP),proposed by Anthropic in late 2024,has emerged as a promising framework.Designed to standardize the interaction between LLMs and their external environments,it serves as a“USB-C interface for AI”.While MCP has been rapidly adopted in the industry,systematic academic studies on its security implications remain scarce.This paper presents a comprehensive review of MCP from a security perspective.We begin by analyzing the architecture and workflow of MCP and identify potential security vulnerabilities across key stages including input processing,decision-making,client invocation,server response,and response generation.We then categorize and assess existing defense mechanisms.In addition,we design a real-world attack experiment to demonstrate the feasibility of tool description injection within an actual MCP environment.Based on the experimental results,we further highlight underexplored threat surfaces and propose future directions for securing AI agent systems powered by MCP.This paper aims to provide a structured reference framework for researchers and developers seeking to balance functionality and security in MCP-based systems.展开更多
文摘在5G与数字生态融合背景下,GSMA Open Gateway通过标准化API与统一接入框架,实现应用在全球运营商网络的可移植与规模化部署,降低开发与适配成本,推动运营商能力开放。然而,跨运营商能力调用仍是关键瓶颈。因此,梳理了CAMARA 4类应用程序编程接口(API)分发模式,对比分析了国内外实践差异。其中,国内运营商针对国内5G网络按需质量保障(QoD)3网互通中聚合平台(Aggregator)面临的痛点,提出了以软件开发工具包(SDK)为核心的解决方案。这一方案通过了统一认证和中国香港商用案例的可行性验证。此外,我国还提出了“SDK+Open Gateway”全球推广与模型上下文协议(MCP)模式演进路径,为全球运营商跨网协同提供中国经验,推动生态从技术框架迈向规模商用,助力数字经济高质量发展。
基金supported by the Science Center of the National Natural Science Foundation of China(Grant No.12188101)the National Key R&D Program of China(Grant Nos.2023YFA1607400 and 2022YFA1403800)+2 种基金the National Natural Science Foundation of China(Grant Nos.12274436,11925408,and 11921004)the New Cornerstone Science Foundation through the XPLORER PRIZEperformed on the robotic AI-Scientist platform of the Chinese Academy of Science.
文摘Density-functional-theory(DFT)simulations with the Vienna Ab initio Simulation Package(VASP)are indispensable in computational materials science but often require extensive manual setup,monitoring,and postprocessing.Here,we introduce VASPilot,an open-source platform that fully automates VASP workflows via a multi-agent architecture built on the CrewAI framework and a standardized model context protocol(MCP).VASPilot’s agent suite handles every stage of a VASP study from retrieving crystal structures and generating input files to submitting Slurm jobs,parsing error messages,and dynamically adjusting parameters for seamless restarts.A lightweight Quart-based web interface provides intuitive task submission,real-time progress tracking,and drill-down access to execution logs,structure visualizations,and plots.We validated VASPilot on both routine and advanced benchmarks:automated band-structure and density-of-states calculations(including on-the-fly symmetry corrections),plane-wave cutoff convergence tests,lattice-constant optimizations with various van der Waals corrections,and cross-material band-gap comparisons for transition-metal dichalcogenides.In all cases,VASPilot completed the missions reliably and without manual intervention.Moreover,its modular design allows easy extension to other DFT codes simply by deploying the appropriate MCP server.By offloading technical overhead,VASPilot enables researchers to focus on scientific discovery and accelerates high-throughput computational materials research.
基金supported in part by the National Natural Science Foundation of China under Grant No.62325207.
文摘With the widespread deployment of large language models(LLMs)in complex and multimodal scenarios,there is a growing demand for secure and standardized integration of external tools and data sources.The Model Context Protocol(MCP),proposed by Anthropic in late 2024,has emerged as a promising framework.Designed to standardize the interaction between LLMs and their external environments,it serves as a“USB-C interface for AI”.While MCP has been rapidly adopted in the industry,systematic academic studies on its security implications remain scarce.This paper presents a comprehensive review of MCP from a security perspective.We begin by analyzing the architecture and workflow of MCP and identify potential security vulnerabilities across key stages including input processing,decision-making,client invocation,server response,and response generation.We then categorize and assess existing defense mechanisms.In addition,we design a real-world attack experiment to demonstrate the feasibility of tool description injection within an actual MCP environment.Based on the experimental results,we further highlight underexplored threat surfaces and propose future directions for securing AI agent systems powered by MCP.This paper aims to provide a structured reference framework for researchers and developers seeking to balance functionality and security in MCP-based systems.
