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756,582 tools. Updated 2026-11-07 17:04

"Enhanced MCP-Reasoner with Monte Carlo Tree Search and Beam Search Integration" matching MCP tools:

  • Plans attack paths step by step using Beam Search or Monte Carlo Tree Search, scoring each step and tracking chains for penetration testing.
    MIT
  • Enhance decision-making processes by applying advanced reasoning strategies like Beam Search and Monte Carlo Tree Search to systematically evaluate and optimize outcomes.
    MIT
  • Generate step-by-step reasoning using beam search or Monte Carlo tree search to explore decision paths for constraint satisfaction and optimization problems.
    MIT
  • Facilitates complex problem-solving using advanced reasoning strategies like Beam Search and Monte Carlo Tree Search to analyze and progress through multiple logical steps.
    MIT
  • Run Monte Carlo simulations to quantify decision risk and receive a structured recommendation with expected value, probability of loss, and confidence percentiles.
    Apache 2.0

Matching MCP Servers

  • A
    license
    Not graded
    quality
    D
    maintenance
    Real Monte Carlo simulation of a compound event or conditional probability. Named random variables, a safe expression interpreter, seedable for reproducibility. Priced per call via x402/USDC on Base.
    1
    MIT

Matching MCP Connectors

  • Web search for AI agents. Ranked results with page passages already extracted, plus URL to markdown.

  • Web search and page reading for AI agents, including JSON APIs, RSS feeds and YouTube.

  • Resample trades from a saved backtest result to assess risk via Monte Carlo simulation, returning ruin probability, equity percentiles, and drawdown distribution.
    Apache 2.0
  • Convert a deterministic Excel workbook into a Monte Carlo model: wrap output cells, replace uncertain inputs with chosen distributions, run a validating simulation, and roll back on any failure.
    MIT
  • Search Gravv documentation to find integration guides, recipes, and API reference. Use when errors are unclear or before implementing to discover prerequisites and ordering.
    MIT
  • Build frequency-severity aggregate loss distributions using FFT, Panjer, or Monte Carlo methods, yielding analytic object forms for direct percentile reads without running simulations.
    MIT
  • Plans turning a deterministic Excel workbook into a Monte Carlo risk model by listing uncertain inputs, declared outputs, and a step-by-step checklist for building and simulating it.
    MIT
  • Search IMAGIN.studio documentation for integration guides, API concepts, and troubleshooting steps. Use specific technical terms to get accurate results.
    Apache 2.0
  • Find the right integration tool for any task by searching available actions with semantic search. Describe what you want to do and get relevant tool suggestions.
    MIT
  • Search PayRetailers official guides and skills to find top matching documentation snippets, ensuring integration answers are grounded in verified sources.
    MIT
  • Search Dollar Tree products and facets, or browse categories by navigation ID to retrieve products, pagination metadata, and filter options for follow-up filter requests.
    MIT
  • Run Monte Carlo simulations to model expected premium and refunds for MEV sandwich risk, based on user-defined assumptions about frequency, loss, and deductible.
    MIT
  • Fetch the leboncoin category tree with IDs, names, slugs, and subcategories. Enable include_filters to also get search filters and enum values for the first category.
    MIT