Launch HN:Pomerado(YC F26)——将任何网站转化为供智能体使用的 MCP
Launch HN: Pomerado (YC F26) – Turn any website into an MCP for agents
我们发现了什么
你好 HN,我们是来自 Pomerado(https://pomerado.ai/)的 Alan 和 Akshay。智能体转而依赖浏览器自动化或计算机操作,这可能速度慢、成本高且不可靠。
- 来源:Hacker News(发现于 2026-11-12)
- 证据等级:D · 发现产品或需求信号,暂未获得可核验的商业证据。
- 商业模式:API / Usage-based
- 主题:AI Agent
- 初筛评分:31.2/100 · 收录 1 次
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中文辅助译文(全文)
你好 HN,我们是来自 Pomerado ( https://pomerado.ai/ ) 的 Alan 和 Akshay。我们只需几分钟,就能将你的智能体连接到任意网站:把网站转化为确定性、可自愈的 API,且整个过程完全自助。智能体不再受其智能水平限制,而是受其与系统交互的能力限制。航空公司、银行、电子商务、保险门户、政府网站和传统门户都缺少 API 或 MCP,而这些网站通常是个人助理或业务流程的组成部分。智能体转而依赖浏览器自动化或计算机操作,但这些方式可能缓慢、昂贵且不可靠。即使计算机操作已经完美,大多数公司仍会出于安全与合规方面的顾虑而禁止使用它。我们是在折腾自己的个人助理时发现这个问题的。OpenClaw 发布后,我们想“通过智能体来生活”,让它们替我们完成一切。很快,我们发现它们的用途受限于能够连接的工具。例如,在尝试预订机票时,它们会转而使用计算机操作,却无法完成结账。在重复执行的工作流中,例如一次搜索多家航空公司时,这些问题会被进一步放大。Pomerado 最初是一个旨在改进这些个人助理工作流的项目。开始构建后,我们意识到,即时工具创建对传统垂直领域的 AI 开发者具有显著的应用价值。我们曾任职于 McKinsey 和 Scale AI,在那里推动了医疗保健、专业服务和电信领域的智能体部署。每一次最大的瓶颈,都是让智能体与旧有网站和应用实现良好对接。我们构建了 Pomerado。它是一个自助平台,开发者只需几分钟就能为任意网站(即使这些网站并不归他们所有)创建 API。
用户(或他们的编码智能体)提供一段简短的自然语言描述,回答有关工作流的几个问题,不到一小时即可获得一个 MCP。后续工具调用会使用这个确定性 MCP,通常在 5-30 秒内返回结果。以下是我们产品的操作演示:https://youtu.be/Bi4jci7rgHo
实际运作如下: - 我们的智能体打开浏览器,探索网站,并通过编写 HTTP 请求或 Playwright 脚本来执行一次所请求的任务。这次示例运行确定了如何浏览网站、与相关控件交互并获得所需结果。如果还需要额外的用户输入(例如登录、补充说明),智能体会通过 MCP 向用户询问。 - 随后,智能体会利用这次示例运行以及期间记录的所有数据,创建一个可泛化、可重复使用的 API。整个过程中,一个独立的 Guardian 模型会按照一组防护规则审查编码智能体的调用。我们还会使用合成输入运行一系列测试,以确保 API 具备泛化能力,而非过拟合于单一输入。最终,一个发布智能体会确保该集成发布合理且通用的输入/输出模式。 - 我们也处理需要身份验证和 2FA 的网站。对于身份验证,我们会将其转交给确定性的登录流程,以确保模型和记录器绝不会读取客户凭据。用户可以存储 2FA TOTP 种子,或将账户关联到 Pomerado 电话号码,以便我们替他们自动填写 2FA。 - 如果后续运行失败,系统会启动维护任务来修复并改进工具。维护任务可以修复失效步骤(例如按钮被重命名)、添加额外功能(例如在经济舱之外搜索商务舱航班),或添加新的防护规则(例如预订日期必须在未来)。我们甚至见过有人只说一句“请让它更快”就改进了工具
与计算机操作不同,我们的 MCP 在运行时是确定性的,因此速度更快、成本也更低。首次执行任务时稍微多花一点时间,之后便能获得大得多的收益。它非常适合执行你希望智能体反复完成的高频任务。我们非常期待你来试用!
我们同时提供开源 (MIT) 版本 ( https://github.com/Pomerado/pomerado ) 和免费的托管版本 ( https://app.pomerado.ai )。
目前,Pomerado 的用户包括: - 一名使用智能体准备训练内容并给客户发送消息的私人教练。在 Pomerado 之前,智能体无法可靠地登录并使用该网站,因此这些工作全都只能手动完成 - 将他们的 Grok Bots 连接到传统经销商系统的汽车经销商,包括市场平台、CRM 和 ERP。经销商已经从可能耗时 1hr+ 的计算机操作切换过来 - 使用 Pomerado 接入各种消费类网站的个人助理
有任何问题或想分享反馈,欢迎在评论区留言,谢谢!
译文由上游机器翻译生成,可能有误;判断请以英文原文为准。
英文原文(来源本站未改写)
Hi HN, we’re Alan and Akshay from Pomerado ( https://pomerado.ai/ ).We connect your agents to any website by turning sites into deterministic, self-healing APIs in minutes, fully self-serve.Agents are no longer limited by their intelligence, but rather by their ability to interact with systems.Airlines, banks, e-commerce, insurance portals, government sites, and legacy portals all lack APIs or MCPs and are common parts of personal assistant or business workflows.Agents instead rely on browser automation or computer use, which can be slow, expensive, and unreliable.And even if computer use were perfect, most companies have banned it out of security and compliance concerns.
We discovered this problem while tinkering with our own personal assistants.When OpenClaw came out, we wanted to “live our lives through our agents” and have them do everything for us.We soon found their usefulness was restricted by what tools they could connect to.For example, when trying to book flights, they fell back on computer use, which failed to checkout.These issues got magnified on repeated workflows, like searching many airlines at once.Pomerado started off as a project to improve these personal assistant workflows.As we started building, we realized that just-in-time tool creation could have significant applications for AI builders in legacy verticals.
We’re ex-McKinsey and Scale AI, where we drove agent deployments in healthcare, professional services, and telecom.Each time, the biggest bottleneck was getting agents to interface well with legacy websites and apps.Pomerado is what we built.It’s a self-serve platform where devs can create APIs for any website (even those they don’t own), in minutes.Users (or their coding agents) provide a short natural language description, answer a few questions about their workflow, and receive a MCP in less than an hour.Future tool calls use the deterministic MCP, which usually returns results in 5-30 seconds.
Here’s a walkthrough of our product: https://youtu.be/Bi4jci7rgHo In practice: - Our agent opens a browser, explores the website, and performs the requested task once by writing HTTP requests or a Playwright script.This example run establishes how to navigate the website, interact with the relevant controls, and obtain the desired result.If any additional user input is needed (e.g., login, clarification) the agent will ask the user over MCP. - Afterwards, the agent uses the example run, along with all of the data it recorded, to create a generalizable and repeatable API.Throughout this process, a separate Guardian model reviews the coding agent’s calls against a set of guardrails.
We also run a battery of tests with synthetic inputs to ensure that the API is generalized and not overfit to one input.A final publication agent ensures that the integration publishes a reasonable and generalized input/output schema - We also handle sites that require authentication and 2FA.For authentication, we pass off to a deterministic sign-in process to ensure the model and our recorders never read customer credentials.Users can store 2FA TOTP seeds or link their account to a Pomerado phone number for us to autofill 2FA for them as well - If future runs fail, a maintenance job is kicked off to repair and improve the tool.
The maintenance job can fix broken steps (e.g., a renamed button), add additional functionality (e.g., searching for business class flights in addition to economy), or add new guardrails (e.g., reservation dates must be in the future).We’ve even seen people improve tools by just saying “please make this faster” Unlike computer use, our MCPs are deterministic at runtime, which makes them much faster and cheaper.By taking slightly longer to do a task the first time, you reap the benefits much more in the future.It’s a great fit for repeated, high-volume tasks you want your agent to do.We’d love to have you try it!
We have both an open-source (MIT) ( https://github.com/Pomerado/pomerado ) and a free hosted version ( https://app.pomerado.ai ).So far, users of Pomerado include: - A personal trainer using agents to prepare workouts and message clients.Before Pomerado, agents couldn’t login and use the site reliably, so this was all manual - Car dealerships connecting their Grok Bots to legacy dealer systems, including marketplaces, CRMs, and ERPs.Dealers switched from computer use, which could take 1hr+ - Personal assistants using Pomerado to integrate with a broad range of consumer websites Please ask any questions or share any feedback in the comments, thanks!
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