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Meta-Cognitive Operating Protocol - A universal reasoning framework for multi-modal hypothesis generation, recursive refinement, and evidence-grounded synthesis.

Project description

mcop

mcop is the Python distribution for the Meta-Cognitive Operating Protocol, a reasoning framework for multi-modal hypothesis generation, recursive refinement, and evidence-grounded synthesis.

The package exposes:

  • A general-purpose reasoning engine.
  • Domain adapters for general, medical, and scientific workflows.
  • A command-line interface for interactive use and scripted runs.
  • Structured outputs with confidence, grounding, evidence, and alternatives.

Install

pip install mcop

Optional extras:

pip install mcop[llm]
pip install mcop[dev]

Quick Start

Solve a problem directly

from mcop import solve

solution = solve("What causes climate change?")
print(solution.content)
print(f"Confidence: {solution.confidence * 100:.1f}%")
print(f"Grounding index: {solution.grounding_index:.2f}")

Work with the engine explicitly

from mcop import MCOPEngine, Problem

engine = MCOPEngine()
problem = Problem(description="Your problem here")
solution = engine.solve(problem)
print(solution.content)

Use a domain adapter

from mcop.domains import MedicalDomainAdapter, PatientPresentation

adapter = MedicalDomainAdapter()
presentation = PatientPresentation(
    chief_complaint="Chest pain",
    symptoms=["chest pain", "shortness of breath"],
)
problem = adapter.create_patient_problem(presentation)
solution = adapter.solve(problem)
print(adapter.format_differential_diagnosis(solution))

Command Line Interface

mcop solve "What are the causes of inflation?"
mcop solve --domain medical "Patient with fever and cough"
mcop interactive
mcop info

What the Package Returns

Each solution includes the primary response plus supporting metadata such as:

  • Confidence score.
  • Grounding index.
  • Evidence chain.
  • Alternative solutions.
  • Key uncertainties.

Project Resources

Notes

  • The Python package has no required runtime dependencies.
  • Medical and scientific adapters are decision-support examples and do not replace professional judgment.
  • Trusted publishing setup for PyPI is documented in TRUSTED_PUBLISHING_SETUP.md.

License

Business Source License 1.1 (BUSL 1.1) — see LICENSE and NOTICE.md for terms, the Change Date (2030-04-26), and the Additional Use Grant. Releases prior to 2026-04-26 remain available under MIT (see LICENSE-MIT-LEGACY).

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