This server has a single tool 'execute_skill_action' with virtually no implementation. The tool definition is inferred from a comment in mcp_server.py rather than explicitly registered via proper MCP protocol. No input schema is visible in the source code. The tool description is generic (23 chars) and provides no actionable guidance on parameters, return values, or when to use it. The mcp_server.py file does not implement the MCP protocol, it merely prints a JSON status message and exits. There is no actual tool handler, no parameter validation, no error handling, and no response schema. The client.py and example_usage.py files are standalone Python code unrelated to MCP. This is not a functional MCP server.

• Implement a proper MCP server using the official MCP SDK (e.g., mcp-python). The current mcp_server.py is a stub that does not handle MCP requests.
• Define execute_skill_action with a complete JSON Schema input specification. Include parameter names, types, descriptions, and constraints (enums, min/max, patterns).
• Expand the tool description to 50 - 200 characters. Explain what the tool does, when to use it, what parameters it accepts, and what it returns. Example: 'Execute a skill action in the agentic developer environment. Accepts action_type (string, enum: deploy|test|review) and target_branch (string). Returns status, staging_url, and logs.'
• Document the output schema with typed fields (e.g., status: string, staging_url: string, logs: array). LLMs need to know what to expect.
• Add error handling that returns actionable messages. E.g., 'Invalid action_type: got "invalid", must be one of: deploy, test, review. Retry with a valid action.'
• Move business logic from client.py into the MCP server's tool handler. The server must be self-contained and callable via MCP protocol, not a wrapper around a separate client class.