This server has a single tool 'execute_skill_action' with virtually no definition. The tool name is vague (execute_skill_action does not follow verb_noun pattern and is generic). No input schema is visible in the source code, the mcp_server.py only prints a JSON status message with a tool list, but contains no actual tool registration, parameter definitions, or output schema documentation. The description 'Execute code autocompletion skill action' is generic and under 50 characters, providing no context for when or why an LLM should call it. No parameters are documented. The client.py and example_usage.py show a separate Python client class that is NOT integrated into the MCP server, they are disconnected implementations. The server does not implement the MCP protocol; it merely prints a static JSON message and exits. This is not a functional MCP server.

• Implement a proper MCP server that handles the protocol handshake, maintains a message loop, and invokes tools via the standard MCP request/response cycle. The current mcp_server.py is a stub.
• Define the tool with a specific, action-oriented name: 'predict_code_completion' or 'complete_code_from_context'. Avoid generic verbs like 'execute' and 'action'.
• Add a detailed description (100-200 chars) explaining: what the tool does (predicts multi-line code completions), when to use it (when the user is writing code and needs suggestions), what it requires (local AST context), and what it returns (predicted code block with acceptance score).
• Define input parameters with types and descriptions: 'local_ast_context' (string, required, description: 'The code context or function signature to complete'), 'air_gapped_security_mode' (boolean, optional, default: true, description: 'Enable air-gapped mode for zero-data-retention').
• Document the output schema with all fields: 'completion_id' (string), 'predicted_code_block' (string), 'acceptance_probability_score_pct' (number 0-100), 'prediction_latency_ms' (integer), 'air_gapped_isolated' (boolean), 'zero_data_retention_verified' (boolean).