Neumann

Connect Remote server

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"
    }
  }
}

Settings > Connectors > Add custom connector
URL: https://neumann.kromatic.com/mcp

Tools 11 found in our last check

• 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…

• 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 n…

• 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 valu…

• 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 l…

• 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 a…

• 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…

• 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…

• 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. Ins…

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