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"Sumo Logic" matching MCP servers:

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    Enables formal logical reasoning, mathematical problem-solving, and proof construction across 11 logic systems including propositional, predicate, modal, fuzzy, and probabilistic logic. Integrates external solvers (Z3, ProbLog, Clingo) for advanced reasoning, with support for proof storage, argument scoring, and cross-system translation.
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    MIT
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    MCP-Logic is a server that provides AI systems with automated reasoning capabilities, enabling logical theorem proving and model verification using Prover9/Mace4 through a clean MCP interface.
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    MIT
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    Connects LLMs to Eclipse SUMO traffic simulation, enabling AI agents to automate traffic network generation, demand modeling, signal optimization, simulation execution, and real-time TraCI control through natural language.
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    MIT
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    An MCP server that exposes vehicle-diagnostic and CAN-bus domain logic as agent tools, with a LangGraph orchestration layer and a human-in-the-loop eval harness.
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    Provides code-aware context compression by stripping comments, docstrings, and whitespace while maintaining full logic fidelity for AI agents. It features tools for architectural mapping, symbol searching, and token-budgeted multi-file reading.
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    MIT
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    A best-effort universal logic and numerical solver interface using MCP that implements the 'LLM sandwich' model to process queries, call dedicated solvers (ortools, cvxpy, z3), and verbalize results.
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    Apache 2.0
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    BlueMouse is the "Prefrontal Cortex" for LLMs. It uses a 180k+ failure pattern database to validate code logic before execution, acting as a rigorous Quality Gate to prevent hallucinations and unsafe operations.
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    AGPL 3.0
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    Provides symbolic reasoning capabilities by converting natural language logical problems into Answer Set Programming (ASP) format and solving them using the Clingo solver. Enables users to perform formal logical reasoning, verify logical arguments, and get step-by-step explanations for complex logical problems.
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    MIT
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    Brings rubber duck debugging to AI-powered IDEs by providing a tool for articulating problems and clarifying logic in natural language. It helps developers and AI agents reveal hidden assumptions and surface solutions through structured self-explanation and reflection.
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    MIT
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    An MCP server for the Pyke logic programming engine that enables LLMs to perform logical reasoning using knowledge bases with facts, rules, and queries. It supports session management, forward chaining inference, and bulk loading of programs in Logic-LLM format.
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    MIT
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    Enables philosophical reasoning and concept analysis through NARS non-axiomatic logic integration, supporting multi-perspective synthesis, epistemic uncertainty tracking, and contextual semantic exploration with built-in truth maintenance.
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    8