feat: add Spanner and CloudSQL support to value search generation

[hardikgu23]

feat(value-search): extend support to Spanner, MySQL, and Postgres

This PR expands the value search generation feature to support additional database engines.

Changes included:

• Added support for Google SQL (Spanner)
• Added support for Cloud SQL (MySQL and PostgreSQL)
• Updated the prompt workflow to dynamically infer the database engine
• Added engine-specific parameters and SQL match templates

Previously, this feature was only supported for AlloyDB.

[gemini-code-assist]

Summary of Changes

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This pull request significantly enhances the system's compatibility by extending support to MySQL and Google SQL (Spanner) databases. The changes involve updating the user interaction prompts to dynamically infer database engines and collect necessary engine-specific parameters, ensuring that the value search generation process can adapt to the unique requirements of these new database types. This expansion allows for a broader range of data sources to leverage the value search capabilities.

Highlights

• Expanded Database Support: Added support for MySQL and Google SQL (Spanner) databases, alongside the existing PostgreSQL/AlloyDB support, by introducing new dialect configurations and match templates.
• Dynamic Database Engine Inference: Updated the prompt workflow to infer the database engine (e.g., postgresql, mysql, googlesql) based on the user-provided database type, streamlining the configuration process.
• Engine-Specific Parameter Handling: Implemented logic to collect and pass engine-specific parameters, such as 'Column Tokens' for Spanner trigram matching and 'Column Embedding' for MySQL semantic matching, to the generate_value_searches tool.
• New Match Templates: Introduced new SQL match templates for MySQL and Google SQL dialects, including exact string matching, trigram string matching, and semantic string matching (for MySQL).

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[gemini-code-assist]

Code Review

This pull request significantly expands the targeted value search functionality by supporting additional database types: PostgreSQL, MySQL, and Spanner. The workflow has been updated to infer the database engine from the provided database type, and new engine-specific parameters have been introduced for Spanner and MySQL. Corresponding SQL templates for GOOGLE_SQL and MYSQL dialects have been added, and the generate_value_searches function now handles these new parameters. Review feedback suggests adding a final newline to mcp/prompts/targeted_value_search.py for PEP 8 compliance, including the table name in the columns field for new GOOGLE_SQL and MYSQL templates for consistency, and simplifying the MySQL TRIGRAM_STRING_MATCH and SEMANTIC_STRING_MATCH templates by removing redundant outer SELECT * FROM (...) AS wrapped_query wrappers.

[wangauone]

Update the PR title and desc to the format of https://www.conventionalcommits.org/en/v1.0.0/. So the release automation pipeline can help us bump the version automatically after merged.

[wangauone]

LGTM