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
pybun mcp serve --stdioEnvironment 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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