django-orm-lens
Static analysis + MCP server for Django models. Terminal- and AI-agent-friendly.
Listed in the official MCP Registry as io.github.FROWNINGdev/django-orm-lens.
Ships with a zero-dependency parser, a JSON/Markdown/table CLI, and an optional MCP (Model Context Protocol) server so any AI coding agent — Cursor, Aider, Continue, and any other MCP client — can navigate your Django schema without importing Django or spinning up your app.
Companion to the Django ORM Lens VS Code extension.
Paid-tier capabilities, free and MIT
Schema review is a paid category nearly everywhere. A bot that reviews every pull request, analysis that follows a queryset past the function it was built in, a check that catches schema drift, index advice grounded in real table statistics — those normally sit behind a per-seat or per-database subscription.
All of it is here, MIT-licensed, with no tier gate, no seat count, no account and no telemetry:
| Capability usually sold as a paid tier | Here |
|---|---|
| PR review bot for schema changes — posts once, then updates in place | blast-radius + the GitHub Action |
| Analysis that follows a queryset across functions | nplusone |
| Schema drift detection | drift |
| Index proposals from observed QuerySet usage | suggest-indexes |
| Migration risk weighed against real table sizes | blast-radius --stats |
| Blast radius of a destructive migration | blast-radius |
| Cross-layer impact of removing a field | impact |
There is no Pro tier, and none is planned.
Install
# Core CLI (zero third-party deps)
pip install django-orm-lens
# With the MCP server (adds the `mcp` package)
pip install "django-orm-lens[mcp]"
Requires Python 3.9+. Works on Linux, macOS, and Windows.
CLI usage
# Scan a Django project for models (JSON, Markdown, or table)
django-orm-lens scan -f json
django-orm-lens scan -f markdown
django-orm-lens scan -f table
# Describe one model
django-orm-lens describe blog.Post
django-orm-lens describe Post -f json
# Compact hover card (great for pipeing into your editor)
django-orm-lens hover blog.Post
# Flat list — pipes into fzf, grep, etc.
django-orm-lens list | fzf
# ER diagram — Mermaid (default), DBML, D2, or PlantUML
django-orm-lens er > schema.mmd
django-orm-lens er -f dbml > schema.dbml # paste into dbdiagram.io
django-orm-lens er -f d2 > schema.d2 # render: d2 schema.d2 schema.svg
django-orm-lens er -f plantuml > schema.puml
# Diff two schema dumps (exit 1 on changes — CI-friendly)
django-orm-lens diff before.json after.json
# Static analyzers — text, json, sarif, or github annotation output
django-orm-lens nplusone --format github # N+1 findings as PR annotations
django-orm-lens migration-risk -f sarif # SARIF for GitHub Code Scanning
django-orm-lens suggest-indexes blog.Post # Meta.indexes proposals from usage
django-orm-lens signals # sender→signal→handler graph
django-orm-lens migration-deps blog -f mermaid # per-app migration DAG
django-orm-lens cascade blog.Author # delete blast radius by on_delete
Every command accepts --path <dir> and repeatable --exclude <glob>. Defaults
skip migrations/, venv/, .venv/, env/, and node_modules/.
MCP server — for AI coding agents
The MCP server exposes ten read-only tools that any MCP-compatible agent can call while it edits your Django project:
| Tool | Purpose |
|---|---|
list_apps |
Every Django app in the workspace with model counts |
list_models |
Flat app.Model list, optional app filter |
describe_model |
Full field / relation / Meta detail for one model |
find_relations |
Inbound + outbound relations for one model |
cascade_preview |
Blast radius of one delete(), grouped by on_delete |
er_diagram |
ER diagram — mermaid / dbml / d2 / plantuml |
describe_migration_dependency |
Per-app migration DAG: roots, leaves, cross-app deps |
suggest_indexes |
Meta.indexes proposals from observed QuerySet usage |
signal_graph |
Sender→signal→handler graph from @receiver decorators |
nplusone_scan |
Static N+1 findings for the whole workspace |
Start the server manually
django-orm-lens-mcp # dedicated entry point
# or
django-orm-lens mcp # subcommand
Workspace resolution (py-1.3.0+). Priority: explicit workspace_root
argument on the tool call → DJANGO_ORM_LENS_ROOT env var → current working
directory. If none resolves to a Django project (manage.py, django in
pyproject.toml, or any models.py) you get a structured error envelope
back — {"error": "WORKSPACE_NOT_DJANGO", "hint": "…"} — instead of an
empty list, so the agent knows what to do next.
Optional sandbox: set DJANGO_ORM_LENS_ALLOWED_ROOTS (;-separated on
Windows, :-separated elsewhere) to a whitelist of prefixes; any path
outside them is rejected with WORKSPACE_NOT_ALLOWED.
Register it with an agent
Cursor — add to ~/.cursor/mcp.json:
{
"mcpServers": {
"django-orm-lens": {
"command": "django-orm-lens-mcp",
"env": { "DJANGO_ORM_LENS_ROOT": "/abs/path/to/your/project" }
}
}
}
Any MCP client — same shape, generic tool. Point command at the
installed django-orm-lens-mcp binary. Two ways to tell it which Django
project to scan:
- Set
DJANGO_ORM_LENS_ROOTinenv— the whole session uses one project. Simplest for single-repo workflows. - Pass
workspace_rooton each tool call — the agent switches projects per call. Useful for mono-repos and multi-workspace setups.
The tool signatures include workspace_root: str = "" as an optional
parameter, so any agent inspecting tools/list sees it and can supply it.
CI gates
diff and nplusone exit 1 on findings; migration-risk exits 1 on
critical findings (--exit-zero for report-only). Two annotation-ready
formats: --format github prints ::warning/::error workflow commands
(PR annotations with no extra permissions), --format sarif emits
SARIF 2.1.0 for github/codeql-action/upload-sarif.
pre-commit users get two ready-made hooks:
repos:
- repo: https://github.com/FROWNINGdev/django-orm-lens
rev: py-v1.13.2
hooks:
- id: django-orm-lens-nplusone
- id: django-orm-lens-migration-risk
GitHub Actions users get a composite action:
uses: FROWNINGdev/django-orm-lens@action-v1 with command: / format: inputs.
Why?
Django's ORM is Python, and Python is dynamic. AI agents that only see
models.py as raw text miss:
- which fields belong to which model;
- the direction and cardinality of every relation;
- what
Meta.ordering,unique_together, andconstraintsactually contain; - which app owns which model when the project uses split
models/packages.
django-orm-lens gives them a static, deterministic, JSON view of the
schema — no Django boot, no database, no side effects. And you get a nice CLI
for humans too.
Programmatic API
from django_orm_lens import scan_workspace
index = scan_workspace(".")
for app in index.apps:
for model in app.models:
print(f"{app.name}.{model.name} — {len(model.fields)} fields")
# The full parsed tree serialises to the same JSON schema the VS Code
# extension emits, so tools can share it interchangeably.
import json
json.dumps(index.to_dict(), indent=2)
Links
- Repo: https://github.com/FROWNINGdev/django-orm-lens
- Issues: https://github.com/FROWNINGdev/django-orm-lens/issues
- Changelog: https://github.com/FROWNINGdev/django-orm-lens/blob/main/CHANGELOG.md
- VS Code extension: https://marketplace.visualstudio.com/items?itemName=frowningdev.django-orm-lens
MIT licensed.
Metadata
Release files for django-orm-lens 1.13.2
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| django_orm_lens-1.13.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 279.2 kB
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