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PyBun

by VOID-TECHNOLOGY-INC

Overview

Programmatic interaction with the PyBun CLI for automation or AI agent integration, serving as a backend for system-level Python tooling.

Installation

Run Command
pybun mcp serve --stdio

Environment Variables

  • PYBUN_HOME
  • PYBUN_TELEMETRY
  • PYBUN_TELEMETRY_ENDPOINT
  • PYBUN_TELEMETRY_TAGS
  • PYBUN_PYPI_BASE_URL
  • PYBUN_PYPI_CACHE_DIR
  • PIP_INDEX_URL
  • PIP_EXTRA_INDEX_URL
  • UV_INDEX_URL
  • UV_EXTRA_INDEX_URL
  • PYBUN_PEP723_DRY_RUN
  • PYBUN_PEP723_NO_CACHE
  • PYBUN_PEP723_BACKEND
  • PYBUN_X_DRY_RUN
  • PYBUN_BUILD_NO_CACHE
  • PYBUN_SANDBOX_ALLOW_NETWORK
  • PYBUN_SELF_UPDATE_MANIFEST
  • PYBUN_SELF_UPDATE_FETCH
  • PYBUN_SUPPORT_UPLOAD_URL
  • PYBUN_TRACE
  • PYBUN_LOG

Security Notes

The MCP server (`pybun mcp serve`) exposes JSON-RPC methods (`call_run`, `call_gc`, `call_doctor`) that execute `pybun` commands as subprocesses. While Rust's `std::process::Command::args` API generally prevents shell injection, allowing an external entity (e.g., an AI agent) to call `call_run` with arbitrary Python script paths or inline code without robust input validation or mandatory sandboxing is a severe privilege escalation risk. The `--sandbox` feature in `pybun run` provides a lightweight Python-level sandbox (blocking subprocesses, optional network access), but it is an opt-in argument, not enforced by the MCP server's `call_run` method. If the MCP server is exposed to untrusted inputs, it effectively grants arbitrary code execution on the host machine.

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Stats

Interest Score0
Security Score3
Cost ClassMedium
Avg Tokens50
Stars0
Forks0
Last Update2026-01-14

Tags

CLIPythonToolingAutomationAI Integration