explain_query
Understand SQL queries by converting them into plain English explanations to clarify database operations and data retrieval logic.
Instructions
Explain what a SQL query does in plain English
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes |
Output Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Implementation Reference
- src/main.py:354-369 (handler)MCP tool handler for 'explain_query', registered with @mcp.tool() decorator. Takes a SQL query string and delegates to OpenAIClient for explanation.
@mcp.tool() async def explain_query(query: str, ctx: Context) -> str: """Explain what a SQL query does in plain English""" await ctx.info(f"Explaining query: {query[:100]}...") try: openai = await get_openai_client() explanation = await openai.explain_query(query) await ctx.info("Generated query explanation") return explanation except Exception as e: logger.error(f"Error explaining query: {str(e)}") await ctx.error(f"Failed to explain query: {str(e)}") raise - src/openai_client.py:171-211 (helper)OpenAIClient method implementing the core logic: calls OpenAI API with tailored system and user prompts to generate plain English explanation of the SQL query.
async def explain_query(self, query: str) -> str: """Explain what a SQL query does in plain English""" system_prompt = """ You are a SQL educator. Explain the provided SQL query in plain English. Your explanation should: - Describe what the query does step by step - Explain complex operations in simple terms - Mention any important performance considerations - Be accessible to both technical and non-technical users Use clear, friendly language. """ user_prompt = f""" SQL Query to explain: {query} Please explain what this query does. """ try: response = await self.client.chat.completions.create( model=self.model, messages=[ {"role": "system", "content": system_prompt}, {"role": "user", "content": user_prompt} ], temperature=0.3, max_tokens=600 ) explanation = response.choices[0].message.content.strip() logger.info("Generated query explanation") return explanation except Exception as e: logger.error(f"Error explaining query: {str(e)}") raise Exception(f"Failed to explain query: {str(e)}")