Deterministic Logic Evaluation MCP Toolkit (deterministic-logic-mcp)

A Model Context Protocol (MCP) server providing high-performance, deterministic logic evaluation tools for AI assistants and automated systems.

Features & Logic Engines

1. Propositional Logic & AST Evaluator: Parse and evaluate boolean expressions with full variable mapping. Supports &&, ||, !, ^ (XOR), => (IMPLIES), <=> (IFF), and custom operator notation.
2. Truth Table Generator: Compute complete $2^N$ truth tables, check tautologies, contradictions, and satisfiability.
3. DPLL SAT Solver: Convert formulas to Conjunctive Normal Form (CNF) and find satisfying variable assignments or prove UNSAT.
4. JSON Logic Rule Engine: Deterministic evaluation of structured rules (boolean, arithmetic, comparison, array filters/maps, conditional branching) against JSON datasets.
5. Decision Table Engine: Grid-based rule evaluation with support for wildcards, first_match, all_matches, and strict_single_match (determinism verification).
6. State Machine Analyzer & Verifier: Check Finite State Machines (FSMs) for determinism, deadlocks, unreachable states, and state reachability path extraction.

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🛠️ MCP Tools Reference

Tool Name	Description	Key Arguments
evaluate_boolean	Evaluates a boolean logic expression with variable values	expression, env
generate_truth_table	Generates full truth table & computes Tautology / Contradiction	expression, maxVariables
solve_sat	DPLL SAT solver returning satisfying variable assignment or UNSAT	expression
evaluate_json_logic	Evaluates JSON logic rules against context JSON data	rule, data
evaluate_decision_table	Evaluates matrix decision table rules with determinism checks	rows, inputs, mode
analyze_state_machine	Checks FSM for determinism, deadlocks, and unreachable states	initialState, transitions, terminalStates
verify_state_reachability	Finds shortest execution path to target state in FSM	initialState, transitions, targetState
simulate_state_machine	Simulates an input sequence through an FSM step-by-step	initialState, transitions, inputSequence

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🚀 Quickstart & Setup

Building Locally

npm install
npm run build
npm test

Configuring in MCP Clients (e.g. Claude Desktop, Cursor, AGY)

Add the following to your mcpServers configuration file (e.g. claude_desktop_config.json):

{
  "mcpServers": {
    "deterministic-logic": {
      "command": "node",
      "args": ["/home/mrovkill/Projects/deterministic-logic/dist/index.js"]
    }
  }
}

Or run directly via npx / tsx:

{
  "mcpServers": {
    "deterministic-logic": {
      "command": "npx",
      "args": ["tsx", "/home/mrovkill/Projects/deterministic-logic/src/index.ts"]
    }
  }
}

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💡 Example Tool Usage

1. Truth Table Generation

Input: expression = "A => (B => A)"
Output: isTautology = true, isSatisfiable = true, truthTable rows showing all evaluated combinations.

2. DPLL SAT Solving

Input: expression = "(A || B) && (!A || B) && (!B)"
Output: satisfiable = false (UNSAT).

3. JSON Logic Rule Execution

Input:

{
  "rule": {
    "and": [
      { ">": [{ "var": "user.age" }, 18] },
      { "in": [{ "var": "user.role" }, ["admin", "editor"]] }
    ]
  },
  "data": { "user": { "age": 25, "role": "admin" } }
}

Output: result = true.

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📄 License

MIT