@aygp-dr
基本情報
A secure, isolated environment for exploring Python development with Model Context Protocol (MCP) and Language Server Protocol (LSP)
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A secure, isolated container environment that combines Model Context Protocol (MCP) and Language Server Protocol (LSP) for Python development. It enables LLMs to access powerful code intelligence features while maintaining strict security boundaries, and is designed for developers exploring algorithm analysis, Claude Code integration, and MCP/LSP educational materials.
Build the Docker/Podman image with make build, then run the container with make run. Verify MCP server connectivity with make test. Analyze algorithms using make analyze ALGO=<algorithm> or make claude-analyze ALGO=<algorithm>. The project also provides custom Claude commands such as /fix-github-issue, /create-pr, and /analyze-algorithm.
It provides container isolation, non-root user execution, restricted port exposure, and integrated MCP/LSP capabilities for AI-assisted development, whereas a standard Python environment lacks these security boundaries and protocol bridges.
Docker or Podman, Python, Make, and GitHub CLI (`gh`) for secrets management. The container runs on Alpine Linux with Python 3 support.
User code and algorithms reside inside the container. Secrets (e.g., ANTHROPIC_API_KEY, GH_PAT) are managed via GitHub Secrets and passed to the container at runtime.
It uses JSON-RPC over stdio. Example: `tools/call` method with `run_python_code` argument to execute Python code and capture output.
Authentication is handled via GitHub Secrets. Secrets are set up using `./scripts/setup_secrets.sh` or manually with `gh secret edit`, and then injected into the container at build/run time.
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