This server has critical definition failures. The single tool 'execute_skill_action' has no visible input schema, no parameter descriptions, and a generic 1-line description (18 chars, below the 20-char minimum). The mcp_server.py file contains only a JSON status message with no actual MCP protocol implementation, no tool registration, no request/response handling, no schema definitions. The client.py and example_usage.py files are standalone Python code unrelated to MCP. No evidence of proper tool definition, parameter validation, or error handling. This is a non-functional MCP server stub.

• Implement actual MCP protocol handling in mcp_server.py: parse JSON-RPC requests, dispatch to tool handlers, return structured responses with proper error codes.
• Add comprehensive input schema to execute_skill_action with typed parameters: text_prompt (string, 10-500 chars), target_polycount (integer, 1000-100000). Include descriptions for each.
• Expand tool description to 50-150 characters explaining WHAT it does, WHEN to use it, and WHAT it returns. Example: 'Generate a 3D mesh with PBR textures from a text prompt. Returns GLTF binary model URL, triangle count, and synthesized texture maps (Albedo, Normal, Roughness, Metallic, Emission).'
• Document output schema with all fields: asset_generation_id (string), prompt (string), mesh_format (enum: GLTF_BINARY), triangle_count (integer), pbr_maps_synthesized (array of strings), watertight_manifold_verified (boolean), generation_time_seconds (number), gltf_model_url (string, URI format).
• Add error handling: return actionable errors for invalid polycount ranges, unsupported prompts, or generation timeouts. Example: 'Invalid target_polycount: 50000 exceeds maximum 100000. Try a lower value.'