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Django Shell

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.

Cognium trust score

65%

Tier

Scanned

Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-19.

Scan details: Circle-IR · 2026-09-19 · Appeal

View full trust & usage report →

Metadata

Version: 1.0.0
Skill type: atomic
Execution layer: mcp-remote
Category: database
Source: PulseMCP
Repository: github.com/joshuadavidthomas/mcp-django
Author type: human
Last scanned: 2026-09-19
Updated: 2026-09-19

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MCP

Resolve Django Shell from your agent

Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.

One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.

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

Swap --scope user for --scope project to commit it to .mcp.json.

Your client Same endpoint everywhere; only the config key differs. The full list is in the descriptor.

Claude Desktop · Settings → Connectors → Add custom connector

https://api.skillsregistry.net/mcp

Paste the URL as the connector endpoint. No authentication.

ChatGPT · Settings → Connectors → Create (developer mode) → MCP server URL

https://api.skillsregistry.net/mcp

Authentication: none. Works in chat and deep research — the server exposes the connector search and fetch tools.

Codex CLI · ~/.codex/config.toml

[mcp_servers.skillsregistry]
url = "https://api.skillsregistry.net/mcp"