from __future__ import annotations
from mcp.server.fastmcp import FastMCP
from .schemas import LPModel, SolveOptions
from .solvers.lp.simplex import solve_lp
from .solvers.mip.branch_and_cut import solve_mip
from .solvers.lp.parser import parse_nl_to_lp
from .solvers.lp.diagnostics import analyze_infeasibility
app = FastMCP("Crew Optimizer")
@app.tool()
def solve_linear_program(model: LPModel, options: SolveOptions | None = None) -> dict:
"""Solve a linear program and return the solution as JSON."""
opts = options or SolveOptions()
solution = solve_lp(model, opts)
return solution.model_dump()
@app.tool()
def solve_mixed_integer_program(
model: LPModel,
options: SolveOptions | None = None,
use_or_tools: bool = False,
) -> dict:
"""Solve a MILP using branch-and-bound or OR-Tools fallback."""
opts = options or SolveOptions(return_duals=False)
solution = solve_mip(model, opts, use_or_tools=use_or_tools)
return solution.model_dump()
@app.tool()
def parse_natural_language(spec: str) -> dict:
"""Parse a natural-language LP specification into structured JSON."""
model = parse_nl_to_lp(spec)
return model.model_dump()
@app.tool()
def diagnose_infeasibility(model: LPModel) -> dict:
"""Return heuristic infeasibility analysis for the given LP."""
return analyze_infeasibility(model)
if __name__ == "__main__":
app.run()
