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    MCP server that enables Claude to control Altair AI Studio for data mining and machine learning tasks, including data import, cleaning, transformation, model training, clustering, association rules, and executing saved processes.
    18
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    Provides deterministic, plain-English narratives explaining machine learning model predictions via the Model Context Protocol. It enables users to query classification factors directly through natural language, bypassing the need for complex plots or manual code execution.
    20
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    Enables AI-driven workflows to extract keyphrases more accurately and with higher relevance using the BERT machine learning model. It works directly with your local files in the allowed directories saving the context tokens for your agentic LLM.
    1
    MIT
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    A specialized Model Context Protocol server that enhances AI-assisted medical learning by connecting Claude Desktop to PubMed, NCBI Bookshelf, and user documents for searching, retrieving, and analyzing medical education content.
    7
    MIT
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    Enables AI scientists to access over 1000 machine learning models, datasets, APIs, and scientific packages for data analysis, knowledge retrieval, and experimental design from any large language model.
    1,644
    Apache 2.0
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    Enables quantum machine learning operations using Qiskit, including executing quantum circuits, computing quantum kernels, training variational quantum classifiers, and evaluating quantum ML models.
    MIT
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    Provides access to over 500 pre-configured YAML templates and guided workflows for fine-tuning, training, and evaluating LLMs like Llama and DeepSeek. It enables AI assistants to search for recipes, retrieve configurations, and validate parameters for various machine learning tasks.
    Apache 2.0
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    Enables quantum systems analysis and simulation including quantum circuits, open quantum systems, quantum chemistry calculations, many-body physics, quantum machine learning, and quantum field theory computations.
    1
    MIT
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    Enables solving linear programming (LP) and mixed-integer linear programming (MILP) optimization problems through natural language, with built-in simplex and branch-and-cut solvers plus infeasibility diagnostics. Includes optional OR-Tools fallback for larger problems and supports parsing optimization problems from natural language descriptions.
    MIT
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    Provides linear programming (LP), mixed-integer programming (MIP), and quadratic programming (QP) optimization capabilities using the HiGHS solver, enabling AI assistants to solve complex optimization problems like production planning, logistics, and portfolio optimization.
    36
    16
    MIT
  • F
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    Enables AI-powered analysis and prediction of household energy consumption through machine learning models, providing historical consumption breakdowns, price queries from Spanish electricity markets, and personalized energy optimization recommendations.
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    An MCP chatbot server that answers questions about a Reinforcement Learning graduate project by dynamically selecting and calling structured tool functions to retrieve precise project data, including training rounds, hyperparameters, and infrastructure details.