This server has critical definition gaps. The single tool 'execute_skill_action' lacks a proper MCP tool registration pattern. The source code shows only a mock JSON response in mcp_server.py with no actual tool schema definition, input validation, or output schema documentation. The client.py and example_usage.py files demonstrate intended functionality but are NOT part of the MCP server implementation. The tool description is generic (41 chars) and parameters lack type definitions in the actual server code. No error handling, no input validation, no structured output schema visible in the server implementation.

• Implement a proper MCP server with a request/response loop. Use the official MCP Python SDK or implement the STDIO protocol correctly: read JSON-RPC requests from stdin, process them, and write responses to stdout.
• Define the tool schema explicitly in the server code using JSON Schema. Include type definitions for all parameters (raw_sql_ddl_schema: string, query_target_entities: array of strings) and document constraints (e.g., max DDL size, valid entity names).
• Expand the tool description to 100-200 characters. Explain: 'Compresses a database schema graph by removing non-critical tables and relationships, reducing token count while preserving foreign key integrity. Use this to fit large schemas into LLM context windows. Returns a simplified schema representation and token reduction percentage.'
• Document the output schema with typed fields: compressed_context_prompt (string), token_reduction_pct (number 0-100), foreign_key_edges_preserved (integer). Include descriptions for each field so LLMs know what to expect.
• Add input validation and error handling. Return structured errors like 'Invalid SQL DDL: syntax error at line 5. Ensure all CREATE TABLE statements are valid.' Include recovery hints (e.g., 'Try removing comments or simplifying the schema').