modelport

# Core only (no ML dependencies)
pip install modelport

# With scikit-learn support
pip install "modelport[sklearn]"

# With XGBoost support
pip install "modelport[xgboost]"

# With LightGBM support
pip install "modelport[lightgbm]"

# With everything
pip install "modelport[all]"

uv sync

from sklearn.datasets import load_iris
from sklearn.linear_model import LogisticRegression

from modelport import Capability

model = LogisticRegression(max_iter=200).fit(*load_iris(return_X_y=True))

capability = Capability.from_model(
    model,
    capability_id="iris-classifier",
    purpose="Predict iris species from flower measurements.",
    when_to_use=("You have sepal/petal measurements",),
    when_not_to_use=("You need regression or continuous outputs",),
)

result = capability.invoke({"sepal_length": 5.1, "sepal_width": 3.5, "petal_length": 1.4, "petal_width": 0.2})
print(result)

from modelport.server.mcp_server import MCPCapabilityServer

server = MCPCapabilityServer(capability)
mcp = server.as_fastmcp(name="iris-classifier")
mcp.run(transport="stdio")

{
  "servers": {
    "iris-classifier": {
      "command": "uv",
      "args": [
        "run",
        "python",
        "examples/04_multi_model_mcp/server.py",
        "--transport",
        "stdio"
      ]
    }
  }
}

from modelport import CapabilityError, ErrorCode

# Errors are automatically structured by modelport
# MCP clients receive:
{
    "error": {
        "code": "VALIDATION_ERROR",
        "message": "Invalid input provided",
        "recoverable": "recoverable",
        "details": {
            "validation_errors": [...]
        }
    }
}

from pydantic import BaseModel

class IrisInput(BaseModel):
    sepal_length: float
    sepal_width: float
    petal_length: float
    petal_width: float

class IrisPrediction(BaseModel):
    species: str
    probability: float

capability = Capability.from_model(
    model,
    capability_id="iris-classifier",
    purpose="Predict iris species",
    input_model=IrisInput,
    output_model=IrisPrediction,
)

uv run pytest tests/ -v
uv run ruff check src/modelport/ tests/
uv run mypy src/modelport/