nexusx

nexusx turns a SQLModel database into two things: a GraphQL query interface that's friendlier than writing SQL, and business logic that ships as REST, GraphQL, MCP, and CLI from a single signature.

flowchart LR
    subgraph Logic["Business logic — one signature, many transports"]
        s["UseCaseService<br/>methods"]
        s --> rest["REST / OpenAPI"]
        s --> gql2["GraphQL"]
        s --> mcp2["MCP (AI agents)"]
        s --> cli["CLI"]
    end
    subgraph Query["Query surface — friendlier than SQL"]
        e["SQLModel entities<br/>+ relationships"]
        e --> gql1["GraphQL"]
        e --> mcp1["MCP"]
        e --> er["ER diagrams (Voyager)"]
    end

What it does for you

1. A query interface over your database — not another query writer.

GraphQLHandler reflects your entities and relationships into a read surface where you declare the shape you want — users { posts { comments } } — and nexusx compiles it to optimal SQL: one batched round-trip per level, columns pruned to what you selected, per-parent pagination. N+1 and over-fetching aren't pitfalls to avoid; they're structurally impossible. Turn on auto_query_config for by_id and equality by_filter; richer predicates (range, like, ordering) are one @query method that rejoins the same surface. Voyager renders the schema as an interactive ER diagram, so the query interface is self-documenting.

2. Business logic, on every transport.

A UseCaseService method is plain async Python. One signature becomes a FastAPI route (with OpenAPI), an MCP tool for AI agents, a CLI command — and a GraphQL field. Note this GraphQL is different from the one above: it projects business operations, not your raw data graph, and it's built AI-first (compact describe_* discovery, no 50K-token introspection dump). The same codebase serves a web frontend, power integrations, and an AI agent without rewriting the logic three times.

Both pillars speak "GraphQL," but they are different surfaces:

In 30 seconds

The query surface — entities become a GraphQL and MCP query interface:

from sqlmodel import SQLModel, Field, Relationship, select
from nexusx import query, GraphQLHandler
from nexusx.mcp import create_simple_mcp_server

class User(SQLModel, table=True):
    id: int | None = Field(default=None, primary_key=True)
    name: str
    posts: list["Post"] = Relationship(back_populates="author")  # ← the entire resolver

    @query
    async def users(cls, limit: int = 10) -> list["User"]:
        async with session() as s:
            return (await s.exec(select(cls).limit(limit))).all()

class Post(SQLModel, table=True):
    id: int | None = Field(default=None, primary_key=True)
    title: str
    author_id: int = Field(foreign_key="user.id")
    author: User | None = Relationship(back_populates="posts")

# GraphQL — { users { posts { title } } } is 2 SQL round-trips, not 1+N
GraphQLHandler(base=SQLModel, session_factory=session)

# MCP — Claude / Cursor call get_schema + graphql_query, fetching SDL on demand
create_simple_mcp_server(base=SQLModel, name="Blog", session_factory=session)

The business-logic surface — one service class becomes REST + MCP:

from nexusx import (
    query, UseCaseService, UseCaseAppConfig,
    create_use_case_router, create_use_case_graphql_mcp_server,
)

class SprintService(UseCaseService):
    @query
    async def list_sprints(cls) -> list[SprintSummary]:
        """Get all sprints with task counts."""
        ...

cfg = UseCaseAppConfig(name="project", services=[SprintService])
app.include_router(create_use_case_router(cfg))        # REST + OpenAPI
create_use_case_graphql_mcp_server(apps=[cfg]).run()   # MCP for AI agents

When to reach for it

• You want a friendlier query interface over a SQLModel database than writing SQL — graph-shaped reads, N+1-proof, selection-driven.
• You need more than one transport from one codebase — REST + GraphQL, or app + AI agent.
• You have non-ORM relations (Redis, search, external APIs) that should flow through the same loader / DTO / diagram plumbing as native ones.

When not to

• You only ever need one REST handler per endpoint and are happy writing them by hand — plain FastAPI is simpler.
• You want fine-grained resolver control over a large GraphQL schema — Strawberry gives you more knobs.

Install

pip install nexusx
pip install nexusx[fastmcp]   # MCP support

Requires Python ≥ 3.10.

Learn more

• Quick Start — entities, DTOs, the UseCase layer
• Feature highlights — the design decisions, in depth
• Voyager visualization — interactive ER + service diagrams
• Auto query — by_id / by_filter without writing @query
• Clean Architecture comparison
• Changelog
• Demos: bash start_all.sh · 4-phase AI skill

Status

Stable — follows semantic versioning. Bug reports and PRs welcome. MIT.