A
licenseNot graded
qualityD
maintenanceMCP server for secure, session-based Python code execution in Docker containers, enabling LLM applications to run code, manage state, and access files.
9
MIT
mcp-python-repl
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TDQS
A4/5.0
Scored across 12 tools
Disambiguation5/5
Each tool targets a distinct operation: running code vs. running files, managing variables (list/get/set/delete/clear), managing sessions (list/delete), plus package installation, history, and server status. There is no overlap between tools; even run_code vs. run_file is clearly separated by input type.
Naming Consistency4/5
All tools follow a 'repl_' prefix and mostly use verb_noun naming (run_code, list_namespace, get_variable, delete_session). The only deviation is 'repl_server_status', which uses noun_noun instead of verb_noun, but this is a minor inconsistency in an otherwise uniform pattern.
Tool Count5/5
With 12 tools, the server is well-scoped for a Python REPL session manager. Each tool addresses a distinct need—execution, package management, namespace introspection, session lifecycle, history, and status—without redundancy or bloat, fitting comfortably in the ideal 3-15 range.
Completeness4/5
The tool surface covers core REPL workflows: running code, running files, installing packages, managing namespace variables, listing/deleting sessions, retrieving history, and server status. Minor gaps exist, such as no explicit 'create session' tool (though sessions appear to be implicit) and no batch execution or session renaming, but these are not critical for typical usage.
Maintenance
ActivityInactive
ResponsivenessNo issues