Water Chemistry MCP Server

Water Chemistry MCP Server

An advanced MCP server powered by PHREEQC for industrial wastewater treatment modeling, offering 17 tools for chemical equilibrium, kinetic reactions, and optimization like lime softening and phosphorus removal.

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Water Chemistry MCP Server

Test Suite Code Quality Integration Tests Python 3.9+ License: MIT

Advanced water chemistry modeling MCP server powered by PHREEQC, designed for industrial wastewater treatment applications. This server provides sophisticated chemical equilibrium and kinetic modeling capabilities through a modern Model Context Protocol (MCP) interface.

⚠️ DEVELOPMENT STATUS: This project is under active development and is not yet production-ready. APIs, interfaces, and functionality may change without notice. Use at your own risk for evaluation and testing purposes only. Not recommended for production deployments.

Features

17 Registered MCP Tools

Core Analysis Tools (5)

  1. calculate_solution_speciation - Complete water quality analysis including pH, ionic strength, saturation indices
  2. simulate_chemical_addition - Treatment simulation with precipitation modeling
  3. simulate_solution_mixing - Stream blending analysis with precipitation
  4. predict_scaling_potential - Mineral scaling risk assessment
  5. batch_process_scenarios - Parallel scenario processing and optimization

Advanced PHREEQC Tools (6)

  1. calculate_dosing_requirement - Binary search for target pH/hardness/SI
  2. query_thermodynamic_database - Query minerals, elements, species from databases
  3. simulate_kinetic_reaction - Time-dependent reaction modeling
  4. simulate_gas_phase_interaction - Gas-water equilibration (CO2 stripping, O2 transfer)
  5. simulate_redox_adjustment - pe/Eh/redox couple adjustment
  6. simulate_surface_interaction - Surface complexation modeling

Optimization Tools (5)

  1. generate_lime_softening_curve - Complete dose-response curves in single call
  2. calculate_lime_softening_dose - Optimal lime dose for target hardness
  3. calculate_dosing_requirement_enhanced - Multi-objective dosing optimization
  4. optimize_multi_reagent_treatment - Multi-reagent with 4 strategies (weighted_sum, pareto_front, sequential, robust)
  5. calculate_phosphorus_removal_dose - Unified P removal with 4 strategies (iron, aluminum, struvite, calcium phosphate)

Diagnostics (1)

  1. get_engine_status - Engine health check and database availability

Phosphorus Removal Strategies

The unified calculate_phosphorus_removal_dose tool supports multiple coagulant/precipitation strategies:

Strategy Reagents Mechanism Typical Metal:P
iron FeCl3, FeSO4, FeCl2 HFO adsorption + Strengite/Vivianite 2.0-3.5
aluminum AlCl3, Al2(SO4)3 HAO adsorption + Variscite 2.5-4.0
struvite MgCl2, MgO, Mg(OH)2 Struvite crystallization 1.0 (stoich)
calcium_phosphate Ca(OH)2, CaCl2 Brushite/HAP precipitation 1.5-2.0

Features:

  • Inline PHREEQC blocks for phases not in standard databases (Struvite, Variscite, HAO surface)
  • SI triggers for metastability control (slow-precipitation phases)
  • Sulfide sensitivity sweep for anaerobic iron (runs [0, 20, 50, 100] mg/L scenarios)
  • HFO/HAO surface complexation with phase-linked site scaling
  • Convergence tracking with converged, target_met, and residual_error_mg_l fields
  • Status semantics: success, success_with_warning, infeasible, input_error
  • P partitioning outputs: phase_moles_mmol_per_L, p_adsorbed_mg_L, p_dissolved_mg_L
  • Redox diagnostics: redox_control_variable, target_pO2_atm for O2 equilibrium mode
  • Chemistry validations: Ca competition warning for struvite, alkalinity check for Ca-P

Advanced Capabilities

  • Multi-database Support: phreeqc.dat, minteq.dat, minteq.v4.dat, llnl.dat, wateq4f.dat, pitzer.dat
  • PHREEQC Subprocess Support: Optional standalone PHREEQC executable for extended compatibility
  • Cross-platform Compatibility: Linux, macOS, and WSL environments
  • Kinetic & Equilibrium Modeling: Both instantaneous and time-dependent processes
  • Multi-objective Optimization: Pareto front, weighted sum, sequential, and robust strategies
  • FAIL LOUDLY Error Handling: Typed exceptions instead of silent failures

Quick Start

Installation

git clone https://github.com/puran-water/water-chemistry-mcp.git
cd water-chemistry-mcp
pip install -r requirements.txt

Start the Server

python server.py

Example Usage

# Lime softening simulation
from tools.chemical_addition import simulate_chemical_addition

input_data = {
    "initial_solution": {
        "units": "mmol/L",
        "analysis": {
            "Ca": 3.0,
            "Mg": 1.6,
            "Alkalinity": 3.3,
            "Cl": 1.0
        },
        "database": "minteq.v4.dat",
        "temperature_celsius": 25.0
    },
    "reactants": [{"formula": "Ca(OH)2", "amount": 5.0, "units": "mmol"}],
    "allow_precipitation": True
}

result = await simulate_chemical_addition(input_data)

Phosphorus Removal Example

# Iron coagulation for P removal
from tools.phosphorus_removal import calculate_phosphorus_removal_dose

input_data = {
    "initial_solution": {
        "ph": 7.0,
        "analysis": {
            "P": 5.0,
            "Ca": 50,
            "Mg": 10,
            "Alkalinity": "as CaCO3 100"
        },
        "units": "mg/L"
    },
    "target_residual_p_mg_l": 0.5,
    "strategy": {
        "strategy": "iron",
        "reagent": "FeCl3"
    },
    "database": "minteq.v4.dat"
}

result = await calculate_phosphorus_removal_dose(input_data)

Optimization Example

# Multi-reagent optimization with Pareto front
from tools.optimization_tools import optimize_multi_reagent_treatment

input_data = {
    "initial_water": {
        "units": "mmol/L",
        "analysis": {"Ca": 2.0, "Mg": 1.0, "Alkalinity": 2.5},
        "pH": 7.0,
        "database": "minteq.v4.dat"
    },
    "reagents": [
        {"formula": "Ca(OH)2", "min_dose": 0.5, "max_dose": 5.0}
    ],
    "objectives": [
        {"parameter": "pH", "value": 10.5, "weight": 0.5},
        {"parameter": "total_hardness", "value": 80, "weight": 0.5}
    ],
    "optimization_strategy": "pareto_front",
    "grid_points": 10
}

result = await optimize_multi_reagent_treatment(input_data)

Scientific Integrity Features

  • PHREEQC-Only Results: All user-facing results use pure PHREEQC thermodynamic calculations
  • Comprehensive Mineral Lists: Default precipitation modeling includes full database minerals
  • Accurate TDS Calculations: Based on individual species concentrations
  • Smart Optimization Bounds: Stoichiometry provides efficient search ranges internally
  • FAIL LOUDLY: All errors raise typed exceptions (DosingConvergenceError, TermNotFoundError, etc.)

Database Support

Database Purpose Elements Minerals
minteq.v4.dat Recommended for softening & P removal (has Brucite) 50+ 300+
minteq.dat General purpose 50+ 300+
phreeqc.dat Standard PHREEQC 40+ 200+
llnl.dat Comprehensive elements 80+ 500+
wateq4f.dat Natural waters 60+ 400+

Testing

# Run all tests
pytest

# With coverage
pytest --cov=tools --cov=utils --cov-report=html

# Specific test files
pytest tests/test_phosphorus_removal.py -v

Project Structure

water-chemistry-mcp/
├── tools/                        # MCP tools (17 total)
│   ├── solution_speciation.py    # Water quality analysis
│   ├── chemical_addition.py      # Chemical dosing
│   ├── solution_mixing.py        # Stream blending
│   ├── scaling_potential.py      # Scaling assessment
│   ├── batch_processing.py       # Parallel processing
│   ├── dosing_requirement.py     # Dosing optimization
│   ├── optimization_tools.py     # Advanced optimization (4 tools)
│   ├── phosphorus_removal.py     # Unified P removal (4 strategies)
│   ├── thermodynamic_database.py # Database queries
│   ├── kinetic_reaction.py       # Kinetic modeling
│   ├── gas_phase.py              # Gas-water equilibria
│   ├── redox_adjustment.py       # Redox control
│   ├── surface_interaction.py    # Surface complexation
│   ├── phreeqc/                  # PHREEQC engine package
│   │   ├── backend.py            # Subprocess execution + engine status
│   │   ├── parser.py             # Output parsing
│   │   ├── simulation.py         # Simulation orchestration
│   │   └── optimizer.py          # Dosing optimization
│   ├── schemas.py                # Core Pydantic schemas
│   └── schemas_ferric.py         # P removal specific schemas
├── utils/                        # Utility modules
│   ├── exceptions.py             # Typed exceptions (FAIL LOUDLY)
│   ├── database_management.py    # Database handling
│   ├── database_registry.py      # Database path registry
│   ├── constants.py              # Mineral mappings
│   ├── helpers.py                # PHREEQC block builders
│   ├── ferric_phases.py          # Fe/Al phase definitions
│   ├── inline_phases.py          # Inline PHREEQC blocks (Struvite, Variscite, HAO)
│   ├── amorphous_phases.py       # Amorphous phase handling
│   ├── convergence_strategies.py # Binary search strategies
│   └── import_helpers.py         # PhreeqPython detection
├── tests/                        # Test suite
├── server.py                     # MCP server entry point
└── CLAUDE.md                     # AI agent documentation

Configuration

Environment Variables

PHREEQC_EXECUTABLE=/usr/local/bin/phreeqc  # Optional: standalone PHREEQC executable
USE_PHREEQC_SUBPROCESS=1                    # Enable subprocess mode
WATER_CHEMISTRY_DEBUG=1                     # Enable debug logging

MCP Client Configuration

For Claude Desktop:

{
  "mcpServers": {
    "water-chemistry": {
      "command": "python",
      "args": ["/path/to/water-chemistry-mcp/server.py"]
    }
  }
}

Current Status

Server Version: 3.1

  • 17 registered MCP tools
  • Unified phosphorus removal with 4 strategies (Fe/Al/Mg/Ca)
  • Inline PHREEQC blocks for Struvite, Variscite, HAO surface
  • NEW: Sulfide sensitivity sweep for anaerobic iron dosing
  • NEW: Convergence tracking and status semantics (success_with_warning)
  • NEW: P partitioning outputs (phase moles, adsorbed P, dissolved P)
  • NEW: Enhanced redox diagnostics with control variable and pO2 fields
  • FAIL LOUDLY error handling with typed exceptions
  • Optional PHREEQC subprocess execution
  • Multi-objective optimization with 4 strategies
  • Comprehensive test coverage (390+ tests)

Documentation

Requirements

  • Python 3.9+
  • PhreeqPython 1.5.2+
  • PHREEQC databases (bundled with PhreeqPython or repo-local)
  • See requirements.txt for full dependencies

License

This project is licensed under the MIT License - see the LICENSE file for details.

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