Neumann

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

• 连接方式: 在云端运行
• 传输方式: Streamable HTTP
• 分类: 会计、财务与税务

安装

选择你使用的 AI 应用，然后复制设置。

你需要

• 在云端运行无需安装任何东西，通过互联网连接

你用的是哪个应用？

https://neumann.kromatic.com/mcp

claude mcp add --transport http neumann https://neumann.kromatic.com/mcp

{
  "mcpServers": {
    "neumann": {
      "url": "https://neumann.kromatic.com/mcp"
    }
  }
}

{
  "servers": {
    "neumann": {
      "type": "http",
      "url": "https://neumann.kromatic.com/mcp"
    }
  }
}

https://neumann.kromatic.com/mcp

你的选择通过 Cookie 保存在这台设备上，无需账户。

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同，请以 README 为准。

它能做什么

工具名称和描述与服务器在 2026年11月6日 报告的完全一致。这些内容由作者撰写，不是我们写的；我们以纯文本形式显示。

• run_monte_carlo_simulation

  Runs a Monte Carlo simulation of a model and returns the full range of possible outcomes, not one guessed number. A model is a set of uncertain inputs, the formulas that combine them, and the links between them. The simulation draws random values for every input many times; each

• rank_inputs_by_impact

  Ranks a model's uncertain inputs by how much each one moves a chosen outcome, and returns the data for a tornado chart. A tornado chart is a bar chart with one horizontal bar per input, sorted with the biggest swing at the top. This is a one-at-a-time (OAT) sensitivity analysis.

• summarize_outcome_scenarios

  Runs a model once and reports one outcome's worst, median and best values. By default, worst is the lowest value in any trial, median is the middle value, and best is the highest value. Worst always means lowest, so for a cost the worst case is the cheapest one. You can ask for o

• check_simulation_model

  Checks a model for mistakes before you run it and lists every problem it finds. It looks for loops with no delay, nodes that are not connected, unknown distributions, missing or invalid distribution parameters, and broken formulas. A loop, including an edge from a node to itself,

• estimate_simulation_size_and_cost

  Predicts how large a run of a model will be and how many credits it will cost, without running it. Use this before running a large or unfamiliar model, or to check that an account can afford it. It does not look for mistakes; use check_simulation_model for that. It returns the nu

• convert_range_to_distribution

  Turns a low-to-high guess, such as "between 80 and 120, 90% sure", into the exact parameters a model input needs. A distribution is the shape of the uncertainty, for example normal (a bell curve), log_normal (skewed and never negative), triangle or uniform. The low and high value

• convert_distribution_to_range

  Turns a distribution's parameters into the low and high ends of the range that holds a chosen share of outcomes, by default the middle 90%. It also gives the mean, median, mode, standard deviation and any percentiles you ask for. If you give a threshold, it gives the chance of la

• get_simulation_results

  Checks on, and reads, a run you started with run_monte_carlo_simulation, rank_inputs_by_impact or summarize_outcome_scenarios, using its run_id. Use this when a run tool returned status running or queued: it waits up to 30 seconds for the run to finish, then returns its status an

• check_account_and_credits

  Shows who Neumann thinks you are and what you can still do: your credit balance if you have an account, or your free runs left today and when they reset if you do not. Use this when you need to know, before or after a run, whether a call will use credits or a free run, how much i

• send_feedback

  Sends a short report about Neumann to the team that builds it. They read every report and use it to fix problems and decide what to build, so honest feedback, good or bad, is useful. Use this when: - a Neumann tool returned an error (send it right away), behaved unexpectedly or g

• buy_credits

  Buys Neumann credits by charging the payment card already saved on your account. Credits pay for simulations run with an account. Use this when an account is low on credits and the user has agreed to the purchase. If no card is saved yet, it buys nothing and charges nothing. Inst

基础检查i

我们检查的是任何人都能看到的信息；我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月8日

• ✓ 通过

  作者与仓库一致

  注册名称已通过 GitHub 账户 Kromatic-Innovation 验证，该账户拥有此仓库

• … 尚未检查

  仍在维护

  我们还没有从 GitHub 读取这个仓库

• … 尚未检查

  有许可证

  我们还没有从 GitHub 读取这个仓库

• ✓ 通过

  端点有响应

  在 139 毫秒内响应（HTTP 200）

• – 不适用

  使用 OAuth 登录

  无需登录

• ✓ 通过

  工具描述中没有隐藏指令

  已读取 11 个工具描述，未发现针对 AI 的隐藏指令

与“会计、财务与税务”中的其他服务器比较i

• 星标数多于此分类中其他 2933 个服务器的 0%
• 发布到注册中心的时间比此分类中其他 2933 个服务器的 77% 更新
• 基础检查结果等于或优于此分类中其他 2933 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时，星标数才计入。

替代选择

同一分类中其他作者的服务器，按星标数排序。

如何看卡片：↓ 每周下载量i★ GitHub 星标i三大支柱：评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

作者的 README

仓库中没有找到 README