[build-system]
requires = ["setuptools>=68", "wheel"]
build-backend = "setuptools.build_meta"

[project]
name = "aurora-mcp"
version = "0.10.1"
description = "Aurora MCP server — glass-box statistical analysis for AI agents: 19 research-grade methods, cited findings, integrity-hashed bundles, zero invented numbers. Now with a calibration engine: measured false-fire rates attached to changepoint findings, verdicts downgraded when the data can't support the claim. Local-first."
readme = "README.md"
requires-python = ">=3.10"
license = { text = "Apache-2.0" }
authors = [{ name = "FantasyLab" }]
keywords = [
    "mcp", "model-context-protocol", "mcp-server", "llm-agents",
    "statistics", "data-analysis", "anomaly-detection", "forecasting",
    "change-point-detection", "causal-inference", "verification",
    "glass-box", "explainable", "local-first",
]
classifiers = [
    "Development Status :: 4 - Beta",
    "Intended Audience :: Developers",
    "Intended Audience :: Science/Research",
    "License :: OSI Approved :: Apache Software License",
    "Operating System :: OS Independent",
    "Programming Language :: Python :: 3",
    "Programming Language :: Python :: 3.10",
    "Programming Language :: Python :: 3.11",
    "Programming Language :: Python :: 3.12",
    "Topic :: Scientific/Engineering :: Information Analysis",
]

# The MCP server pulls in the full Aurora engine — these mirror
# requirements.txt minus the Studio web server (flask lives in the
# optional [http] extra for the remote-transport shim).
dependencies = [
    "numpy>=1.24",
    "pandas>=2.0",
    "scipy>=1.10",
    "scikit-learn>=1.3",
    "statsmodels>=0.14",
    "ruptures>=1.1",
    "sympy>=1.12",
    "matplotlib>=3.7",
    "pyarrow>=14.0",
    "openpyxl>=3.1",
    "requests>=2.31",
    "mcp>=1.0,<2",
]

[project.optional-dependencies]
http = ["flask>=3.0", "flask-cors>=4.0"]

[project.scripts]
aurora-mcp = "aurora_mcp.server:main"

[project.urls]
Homepage = "https://github.com/FantasyLab-ai/aurora"
Repository = "https://github.com/FantasyLab-ai/aurora"
Documentation = "https://github.com/FantasyLab-ai/aurora/blob/main/docs/mcp.md"
Changelog = "https://github.com/FantasyLab-ai/aurora/blob/main/CHANGELOG.md"

[tool.setuptools.packages.find]
include = ["aurora_mcp*", "aurora_sdk*", "fantasyai*"]

# Runtime data the engine reads at import/analysis time — domain context
# libraries, equation translations, knowledge-bank pack manifest.
[tool.setuptools.package-data]
"*" = ["*.json"]
"fantasyai.aurora.synthesis" = ["domain_libraries/*.json", "equation_translations/*.json"]
"fantasyai.aurora.knowledge_bank" = ["packs/*.json"]
# The calibration corpus ships with its integrity sidecar + manifest —
# load_corpus refuses a table it cannot hash-verify.
"fantasyai.aurora.calibration" = ["*.json", "*.sha256", "MANIFEST.md"]

[tool.pytest.ini_options]
testpaths = ["tests"]
# Only collect ``test_*.py`` — the ``_run_manual*.py`` and ``_smoke_*.py`` files are
# standalone scripts that run their own assertions and would conflict with pytest's
# discovery. They're useful when pytest isn't available locally.
python_files = ["test_*.py"]
python_classes = ["Test*"]
python_functions = ["test_*"]
addopts = [
    "-q",                         # quiet output
    "--strict-markers",
    "--strict-config",
    "-ra",                        # short summary of all skip/xfail/fail
    "--tb=short",
]
markers = [
    "slow: tests that run a real subprocess (deselect with '-m \"not slow\"')",
    "integration: end-to-end pipeline tests against real fixture data",
]
filterwarnings = [
    "ignore::DeprecationWarning",
    "ignore::PendingDeprecationWarning",
]

[tool.aurora]
# Project-specific config consumed by tooling.
provenance_ledger_filename = "_provenance_ledger.jsonl"
priors_count_v1 = 9
fixtures_count_v1 = 3