Evaluate and integrate hdresearch/mcp-python for Python REPL-based MCP workflow

## Overview

This issue proposes evaluating and integrating the [hdresearch/mcp-python](https://github.com/hdresearch/mcp-python) repository (and its enhanced fork [piplin-es/mcp-python](https://github.com/piplin-es/mcp-python)) as part of our MCP dotfiles configuration to support Python REPL-based workflows.

## Proposed Integration

The Python REPL MCP server would provide:
- Persistent Python sessions (supporting our "Snowball Method" principle)
- Environment variable management via `.env` files
- Package installation capabilities
- File and project management tools
- Integration with any MCP-compatible client (Amazon Q, Claude, GitHub Copilot)

## Implementation Plan

1. Create a setup script in `~/ppv/pillars/dotfiles/mcp/setup-python-mcp.sh`
2. Add documentation in `~/ppv/pillars/dotfiles/mcp/README-python-mcp.md`
3. Configure integration with Amazon Q and other MCP clients

## Important Implementation Notes

**To minimize risk of hallucinated configuration settings:**
- Clone the source repository directly when setting up the PR
- Verify all setup variables and values from the source code
- Check the actual tool names and parameters from the repository code
- Test the integration with actual MCP clients before merging

## Alignment with Dotfiles Philosophy

This integration aligns with our core principles:
1. **The Spilled Coffee Principle**: Easy setup and recovery with a single script
2. **The Snowball Method**: Persistent REPL session accumulates knowledge over time
3. **The Versioning Mindset**: Supports incremental improvements through file operations

## Next Steps

- [ ] Create a feature branch
- [ ] Implement the setup script and documentation
- [ ] Test with Amazon Q and other MCP clients
- [ ] Submit PR for review

Start by inspecting the referenced hdresearch/mcp-python repository and its piplin-es fork, then review the existing MCP dotfiles configuration. Implement the named setup-python-mcp.sh script and README-python-mcp.md, verifying setup variables, tool names, parameters, and actual integration with Amazon Q or another MCP client. Done means the documented setup works and the client integration has been tested.

Written by the indexing model from the issue text.