#MCP/工具调用

中国的互联网从13年的移动端时代就变成了“不联网”，其实现在美国的互联网也因为Agent能力重新可能变成“不联网”。 中国移动互联网 “不”联网的特征是： - 不能发现内容，搜索引擎找不到，必须进入某个 App 搜； - 不能读取内容，有链接也看不了，折叠全文、弹出登录或下载要求； - 不能使用功能，网页只有介绍或残缺功能，完整操作必须进 App／小程序； - 不能跨平台流动，链接被拦、不能直接跳转、只能复制口令或换浏览器。 这一个现象一直都很恶心，很独特的你封杀我我封杀你，平台之间的“截流”和投流量成为了一门学问，形成了我只在中国产品里见到的靠口令红包和自动读取剪贴板跳转的生态，贼tmd sb。 这也是为什么中国不管是Personal Agent还是Work Agent都是在同一体系内很能打，但是一旦跨体系就几乎智障的原因，很难出现一个Open Web上的Super Agent，都关着门，没有数据可以拿到没有功能可以调用，哪里能构建好Context和Workflow。 中国当前App “不联网” 的本质原因有两个。 一是因为2013年后手机端成为了主要入口，每一个大厂都在打造自己的超级App，于是乎web端功能不再迭代甚至删减限制，每一产品都在把聊天、内容、购物、支付乃至部分公共服务全部塞到自己生态里，再通过小程序继续确保用户不离开自己。 另外一个就是17年基本所有主流平台受网络安全法要求统一强制实名要求，其实也给了大厂们一个理由更封闭。 但是其实美国也在AI时代互联网面临着“不”联网的处境，最近大量讨论都围绕在平台是否应该向Agent开放权限上，大部分的头部传统企业也都先选择把门关上。 购物网站： - Amazon：2025年10月31日向Perplexity发函，要求其购物代理Comet停止未经Amazon许可的代理访问；2026年9月，又封锁了Meta Muse对Amazon的访问。 - eBay：用户协议直接点名代买Agent、LLM驱动的机器人等自动化工具，要求事先获得eBay明确许可才能访问其服务。 - Target：采用Agent白名单。只有用户批准、同时获得Target授权的Agent才能接入，其他Agent不能登录、查询、抓取数据，或者通过API与网站交互。 银行和券商： - 花旗Citi：不允许第三方AI Agent代客户登录账户，或者直接在其数字银行平台内执行交易；保留通过部分开放银行服务商、经客户授权的有限只读访问。 - 摩根大通Chase：要求Agent明确表明身份、标记流量，并在条款中保留限制、暂停、终止Agent访问的权利。 出行和本地生活： - Delta航空：条款明确写着，用户授权某个第三方Agent，并不构成Delta对它的授权；Delta保留拒绝与其交互、处理其请求或交易的权利。 - Yelp：未经许可的自动化访问、抓取和检索受到限制；它也提供自己的MCP接入，但需要通过Yelp的API密钥使用。

Introducing voice, music, image, and video generation in the ElevenLabs MCP. Generate speech, transcripts, dubs, music, sound effects, images, and video from the assistant you already work in.

Introducing Claude Tag, a new way for teams to work with Claude. In Slack, Claude joins as a team member with access to the channels and tools you choose. Tag Claude in and delegate tasks to it while you focus on other work.

Levie now uses Salesforce 5x more than at any point before. The Box CEO @levie connected Salesforce's MCP server to Claude Code. Now he runs customer and market intelligence queries he would never have bothered pulling up by hand. The agent removes the friction. The underlying system gets queried more, not replaced. If you hold $CRM, the agentic era is an engagement tailwind, not a disruption risk - gated on whether the data platform handles the query load. Why incumbents gain from agents: https://podcastalpha.substack.com/p/aaron-levie-on-ai-agents-for-cios Source: CXOTalk - https://www.youtube.com/watch?v=ylBDQHk3BhI

New video of Qualcomm CEO Cristiano Amon: AI will require “gazillions” of tokens. Because, Agentic AI will consume dramatically more tokens because it performs autonomous tasks, uses multiple systems, and interacts with tools. AI demand will grow hugely when software starts letting agents act, not just answer. A chatbot spends tokens on language; an agent spends tokens on deciding, checking, calling tools, reading outputs, revising plans, and coordinating with other software. Today a single human-AI exchange may be large, a reasoning task may be much larger, but we are already entering the agentic era, where an autonomous workflow can become exponentially larger still because the model is no longer producing one response. It is running a process. When a SaaS product redesigns itself around human-agent interaction, every task can become a chain of hidden micro-decisions, and each micro-decision consumes context, memory, tool calls, verification, and output tokens. Another point is people hear “more tokens” and think only of bigger data centers, when the deeper change is economic: software usage may stop being measured mainly by clicks, seats, or sessions. It will be measured by how much machine reasoning/tokens gets spent on behalf of each user. ---- From "Reuters" YouTube channel, (link in comment)

Goldman Sachs: "Token use by AI agents is expected to multiply 24 times by 2030" AI agents are now creating the first serious cost test for the AI boom. As was reported this week, Uber and Microsoft are already rethinking expensive agent usage. A chatbot may answer once, but an agent plans, calls tools, checks results, edits mistakes, and repeats the loop. That loop can make one user request consume 10x, 50x, or even far more tokens than a normal answer. Goldman’s bullish case is that monthly token use could reach 120 quadrillion by 2030, while inference cost per token keeps falling 60%-70% per year. The fight is now between agent productivity and token waste. Earlier this month, Microsoft began revoking developer access to Claude Code, with plans to move them to its in-house Copilot Command Line Interface tool by June 30. The company has framed this as consolidating teams around its own tools, but the timing at the fiscal year’s end hints it may also be about lowering costs.