TechCrunch News 2024年11月26日
Anthropic proposes a new way to connect data to AI chatbots
index_new5.html
../../../zaker_core/zaker_tpl_static/wap/tpl_guoji1.html

 

Anthropic发布了名为模型上下文协议(MCP)的新标准,旨在连接AI助手与数据系统,从而提升AI模型的响应质量和相关性。MCP允许AI模型从业务工具、内容库和开发环境等数据源获取信息,完成任务。该协议通过构建数据源和AI应用之间的双向连接来解决AI模型数据获取难题,开发者可通过MCP服务器公开数据,并构建连接到这些服务器的MCP客户端应用。目前,Block、Apollo等公司已集成MCP,Zed、Replit等开发工具也正在添加支持。Anthropic希望MCP能够成为一个开放的生态系统,促进上下文感知AI的发展。

🤔Anthropic推出模型上下文协议(MCP),旨在连接AI助手与数据源,例如业务工具、内容库和开发环境等,以提升AI模型的响应质量和相关性。

🤝MCP通过构建数据源和AI应用之间的双向连接,解决AI模型数据获取难题,开发者可通过MCP服务器公开数据,并构建连接到这些服务器的MCP客户端应用。

🚀Block、Apollo等公司已集成MCP,Zed、Replit等开发工具也正在添加支持,形成了初步的生态系统。

💡Anthropic希望MCP成为一个开放的生态系统,促进上下文感知AI的发展,并提供预构建的MCP服务器,例如Google Drive、Slack和GitHub等。

⚠️MCP的推广和应用仍面临挑战,需要获得行业内其他公司的认可和支持,并通过实际应用案例证明其有效性。

Anthropic is proposing a new standard for connecting AI assistants to the systems where data lives.

Called the Model Context Protocol, or MCP for short, Anthropic says the standard, which it open sourced today, could help AI models produce better, more relevant responses to queries. MCP lets models draw data from sources like business tools to complete tasks, as well as from content repositories and development environments.

“As AI assistants gain mainstream adoption, the industry has invested heavily in model capabilities, achieving rapid advances in reasoning and quality,” Anthropic wrote in a blog post. “Yet even the most sophisticated models are constrained by their isolation from data — trapped behind information silos and legacy systems. Every new data source requires its own custom implementation, making truly connected systems difficult to scale.”

MCP ostensibly solves this problem through a protocol that enables developers to build two-way connections between data sources and AI-powered applications (e.g. chatbots). Developers can expose data through “MCP servers” and build “MCP clients” — i.e. apps — that connect to those servers.

Anthropic says that companies including Block and Apollo have already integrated MCP into their systems, while dev tool firms including Zed, Replit, Codeium, and Sourcegraph are adding MCP support to their platforms.

“Instead of maintaining separate connectors for each data source, developers can now build against a standard protocol,” Anthropic wrote. “As the ecosystem matures, AI systems will maintain context as they move between different tools and data sets, replacing today’s fragmented integrations with a more sustainable architecture.”

Developers can start building with MCP connectors today, and subscribers to Anthropic’s Claude Enterprise plan can connect the company’s Claude chatbot to their internal systems and data with MCP servers. Anthropic has shared pre-built MCP servers for enterprise systems like Google Drive, Slack, and GitHub, and says that it’ll soon provider developer toolkits for deploying remote production MCP servers that can serve an entire Claude Enterprise workplace.

‘We’re committed to building MCP as a collaborative, open-source project and ecosystem,” Anthropic wrote. “We invite you to build the future of context-aware AI together.”

MCP sounds like a good idea in theory. But it’s far from clear that it’ll gain much traction, particularly among rivals like OpenAI, which would surely prefer that customers and ecosystem partners use their data-connecting approaches and tools.

It also remains to be seen whether MCP is as beneficial as Anthropic says it is. The company asserts, for example, that MCP can enable an AI chatbot to “further understand the context around a coding task,” but it provides no benchmarks supporing that claim.

Fish AI Reader

Fish AI Reader

AI辅助创作,多种专业模板,深度分析,高质量内容生成。从观点提取到深度思考,FishAI为您提供全方位的创作支持。新版本引入自定义参数,让您的创作更加个性化和精准。

FishAI

FishAI

鱼阅,AI 时代的下一个智能信息助手,助你摆脱信息焦虑

联系邮箱 441953276@qq.com

相关标签

AI助手 模型上下文协议 MCP 数据连接 Anthropic
相关文章