Core challenges
Traditional NL2SQL schemes suffer from problems such as biased semantic understanding and lack of database context, leading to inaccurate query results.
MCP Optimization Solution
pass (a bill or inspection etc)context-sensitivecap (a poem)Predefined toolsDual mechanisms to achieve optimization:
- Pattern Binding:Explicitly define the parameter type (e.g., string/date) and field descriptions in tools.yaml, for example:
parameters:
- name: check_in_date
type: date
description: 客户入住日期(YYYY-MM-DD) - Tool Chaining Calls:Decomposition of complex queries into multiple predefined tool combinations
- Dynamic SQL generation:Automatic query optimization based on table structure (e.g. add index hints)
Operation Guide
1. Direct input of natural language using IDE plug-ins (e.g. "Top 10 customers in terms of sales in Q3 2024")
2. The system automatically matches the closest predefined tools
3. Visual validation of the generated SQL before execution
Effectiveness evaluation
Measured to reduce syntax errors by 701 TP3T and query response time by 501 TP3T (compared to the original NL2SQL solution)
This answer comes from the articleMCP Toolbox for Databases: MCP services for fast database operationsThe
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