{"id":292164,"date":"2024-11-27T19:30:22","date_gmt":"2024-11-27T18:30:22","guid":{"rendered":"https:\/\/sftarticles.wpenginepowered.com\/es\/?p=344709"},"modified":"2025-07-01T15:41:36","modified_gmt":"2025-07-01T22:41:36","slug":"this-is-anthropics-proposal-for-ai-to-be-trained-more-easily","status":"publish","type":"post","link":"https:\/\/cms-articles.softonic.io\/en\/this-is-anthropics-proposal-for-ai-to-be-trained-more-easily\/","title":{"rendered":"This is Anthropic's proposal for AI to be trained more easily"},"content":{"rendered":"\n

Anthropic<\/strong> has proposed a new standard to facilitate the connection of artificial intelligence assistants with the systems where the datasets they are trained on reside. According to the company, this open-source protocol, called the Model Context Protocol (MCP)<\/strong>, aims to improve AI model responses by making them more relevant and useful<\/strong>.<\/p>\n\n\n

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Subscribe to the Softonic newsletter and get the latest in tech, gaming, entertainment and deals right in your inbox.<\/p>\r\n Subscribe (it's FREE) \u25ba<\/a>\r\n <\/div>\r\n <\/div>\r\n <\/a>\r\n <\/div>\r\n<\/div>\n\n\n\n

MCP allows models to access data from business tools, content repositories, and application development environments, making it a versatile solution for various tasks<\/strong>. In a statement on their website<\/a>, Anthropic highlighted how current AI assistants, even with their high capabilities, \u201care trapped behind information silos and legacy systems.\u201d<\/p>\n\n\n\n

The integration of new data sources requires custom implementations, making it difficult to scale connected systems. With MCP, the company aims to solve this problem by offering a standard protocol to establish bidirectional connections between data sources and AI-driven applications<\/strong>, such as chatbots.<\/p>\n\n\n

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Introducing the Model Context Protocol (MCP)<\/p>\n

An open standard we’ve been working on at Anthropic that solves a core challenge with LLM apps – connecting them to your data.<\/p>\n

No more building custom integrations for every data source. MCP provides one protocol to connect them all: pic.twitter.com\/kYsivQyPDq<\/a><\/p>\n

\u2014 Alex Albert (@alexalbert__) November 25, 2024<\/a><\/p><\/blockquote>\n\n\n\n

Companies like Block and Apollo have already integrated MCP, while developer tool platforms like Zed, Replit, Codeium, and Sourcegraph are adopting its support. Anthropic explained that the use of MCP will allow developers to avoid creating individual connectors for each data source<\/strong>. \u201cAs the ecosystem matures, AI systems will be able to maintain context between tools and data sets, replacing fragmented integrations with a more sustainable architecture,\u201d the company noted.<\/p>\n\n\n\n

The company has also made preconfigured MCP servers available for enterprise systems like Google Drive, Slack, and GitHub<\/strong>, and will soon launch tools for organizations to implement custom MCP servers. Additionally, subscribers of Claude<\/strong>, Anthropic’s chatbot, can now connect it to internal systems using MCP. \u201cWe are committed to building MCP as an open and collaborative project,\u201d stated Anthropic, inviting developers to join the initiative.<\/p>\n\n\n

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Anthropic has proposed a new standard to facilitate the connection of artificial intelligence assistants with the systems where the datasets they are trained on reside. According to the company, this open-source protocol, called Model Context Protocol (MCP), aims to improve the responses of AI models by making them more relevant and useful. MCP allows models to access data from enterprise tools, content repositories, and application development environments, making it a versatile solution for various tasks. In a statement on their website, Anthropic highlighted […]<\/p>\n","protected":false},"author":9256,"featured_media":292174,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":"","wpcf-pageviews":2},"categories":[1015],"tags":[],"usertag":[],"vertical":[],"content-category":[6771],"class_list":["post-292164","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news","content-category-ai"],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/cms-articles.softonic.io\/en\/wp-json\/wp\/v2\/posts\/292164","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/cms-articles.softonic.io\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/cms-articles.softonic.io\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/cms-articles.softonic.io\/en\/wp-json\/wp\/v2\/users\/9256"}],"replies":[{"embeddable":true,"href":"https:\/\/cms-articles.softonic.io\/en\/wp-json\/wp\/v2\/comments?post=292164"}],"version-history":[{"count":1,"href":"https:\/\/cms-articles.softonic.io\/en\/wp-json\/wp\/v2\/posts\/292164\/revisions"}],"predecessor-version":[{"id":310654,"href":"https:\/\/cms-articles.softonic.io\/en\/wp-json\/wp\/v2\/posts\/292164\/revisions\/310654"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/cms-articles.softonic.io\/en\/wp-json\/wp\/v2\/media\/292174"}],"wp:attachment":[{"href":"https:\/\/cms-articles.softonic.io\/en\/wp-json\/wp\/v2\/media?parent=292164"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/cms-articles.softonic.io\/en\/wp-json\/wp\/v2\/categories?post=292164"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/cms-articles.softonic.io\/en\/wp-json\/wp\/v2\/tags?post=292164"},{"taxonomy":"usertag","embeddable":true,"href":"https:\/\/cms-articles.softonic.io\/en\/wp-json\/wp\/v2\/usertag?post=292164"},{"taxonomy":"vertical","embeddable":true,"href":"https:\/\/cms-articles.softonic.io\/en\/wp-json\/wp\/v2\/vertical?post=292164"},{"taxonomy":"content-category","embeddable":true,"href":"https:\/\/cms-articles.softonic.io\/en\/wp-json\/wp\/v2\/content-category?post=292164"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}