This server is non-functional as an MCP implementation. The mcp_server.py file contains only a print statement that outputs JSON, it does not implement the MCP protocol at all. No tool schemas, parameter definitions, or descriptions are present in the source code. The single tool 'execute_skill_action' has a trivial description (18 chars) but no input schema, output schema, or parameter documentation. The code does not handle MCP requests, parse JSON-RPC, or implement any protocol handlers. This is a stub, not a working MCP server.

• Define a complete JSON Schema for execute_skill_action input parameters. Include type, description, and constraints for each parameter (e.g., skill_id, action_type, parameters). Reference the MCP spec for proper schema format.
• Expand tool description to 50 - 200 characters. Explain: What does this tool do? When should the LLM call it? What does it return? Example: 'Execute a predefined skill action (e.g., data transform, API call, validation) within the visual workflow. Returns action_id, status, and result data. Use this to trigger workflow steps.'
• Document the output schema with typed fields (action_id: string, status: enum[pending|running|success|failed], result: object, error_message: string). Include pagination if results are lists.
• Implement actual MCP protocol handling in mcp_server.py: parse JSON-RPC requests from stdin, dispatch to tool handlers, return structured responses. Use an MCP library (e.g., mcp-python) or implement the spec directly.
• Add error handling that returns actionable messages. Example: 'Skill not found. Available skills: [list]. Try search_skills() first.' Categorize errors as retryable or user-fixable.