# Django Shell

> Use this tool when you need to execute Django ORM operations, explore models, or interact with Django applications in a stateful Python shell environment. It solves problems related to Django development, database exploration, and automated application management by providing a persistent session with intelligent formatting and comprehensive error handling. The tool accepts Python code as input and outputs the results of Django ORM operations, with options to clear session state and maintain execution history.

Canonical page: https://skillsregistry.net/skills/joshuadavidthomas-django-shell  
JSON: https://api.skillsregistry.net/v1/skills/joshuadavidthomas-django-shell

## Description

This Django MCP server provides a stateful Python shell environment specifically configured for Django development, enabling AI assistants to execute Django ORM operations, explore models, and interact with Django applications through persistent sessions. Built by Josh Thomas using FastMCP, it offers two core tools: django_shell for executing Python code with full Django context and django_reset for clearing session state, with intelligent formatting for querysets and comprehensive error handling. The implementation maintains execution history, supports both synchronous and asynchronous operations, and includes robust testing with multiple Django/Python version compatibility, making it valuable for AI-assisted Django development, database exploration, and automated Django application management workflows.

## Trust

- **Trust score (0–1):** 0.65
- **Verification tier:** scanned
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-09-19

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/joshuadavidthomas-django-shell)
- **Repository:** <https://github.com/joshuadavidthomas/mcp-django>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "joshuadavidthomas-django-shell"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/joshuadavidthomas-django-shell` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/joshuadavidthomas-django-shell/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt