SQLAlchemy Integration

include_sqlalchemy_models automatically converts SQLAlchemy models into EnrichModel entities and registers default resolvers. It works with any AsyncEngine, so you can use PostgreSQL, MySQL, SQLite or any other database supported by SQLAlchemy.

from enrichmcp import EnrichMCP
from enrichmcp.sqlalchemy import (
    EnrichSQLAlchemyMixin,
    include_sqlalchemy_models,
    sqlalchemy_lifespan,
)
from sqlalchemy import ForeignKey
from sqlalchemy.ext.asyncio import create_async_engine
from sqlalchemy.orm import DeclarativeBase, Mapped, mapped_column, relationship

engine = create_async_engine("postgresql+asyncpg://user:pass@localhost/db")



class Base(DeclarativeBase, EnrichSQLAlchemyMixin):
    pass

# define SQLAlchemy models inheriting from Base

class User(Base):
    __tablename__ = "users"

    id: Mapped[int] = mapped_column(primary_key=True)
    username: Mapped[str] = mapped_column(unique=True)
    orders: Mapped[list["Order"]] = relationship(back_populates="user")


class Order(Base):
    __tablename__ = "orders"

    id: Mapped[int] = mapped_column(primary_key=True)
    user_id: Mapped[int] = mapped_column(ForeignKey("users.id"))
    total: Mapped[float] = mapped_column()
    user: Mapped[User] = relationship(back_populates="orders")


class Product(Base):
    __tablename__ = "products"

    id: Mapped[int] = mapped_column(primary_key=True)
    name: Mapped[str] = mapped_column()
    price: Mapped[float] = mapped_column()


lifespan = sqlalchemy_lifespan(Base, engine)  # seed optional
app = EnrichMCP("Shop API", "Demo", lifespan=lifespan)
include_sqlalchemy_models(app, Base)

The function scans all models inheriting from Base and creates:

• list_<entity> and get_<entity> resources using primary keys.
• Relationship resolvers for each SQLAlchemy relationship.
• Pydantic EnrichModel classes with descriptions derived from column info.

Pagination parameters page and page_size are available on the generated list_* endpoints.

sqlalchemy_lifespan automatically creates tables on startup and yields a session_factory that resolvers can use. Providing a seed function is optional and useful only for loading sample data during development or tests. If you are using a temporary SQLite file and want it removed on shutdown, pass cleanup_db_file=True.