podbc_virtuoso_support_ai
Leverage AI support in Virtuoso via MCP’s SQLAlchemy integration to process prompts and enhance database interactions.
Instructions
Tool to use the Virtuoso AI support function
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| api_key | No | ||
| prompt | Yes | ||
| url | No |
Implementation Reference
- mcp_sqlalchemy_server/server.py:445-474 (handler)The handler function decorated with @mcp.tool, which registers and implements the 'podbc_virtuoso_support_ai' tool. It connects to the database via pyodbc, executes the Virtuoso AI support SQL function with the prompt and API key, and returns the result.
@mcp.tool( name="podbc_virtuoso_support_ai", description="Tool to use the Virtuoso AI support function" ) def podbc_virtuoso_support_ai(prompt: str, api_key:Optional[str]=None, user:Optional[str]=None, password:Optional[str]=None, dsn:Optional[str]=None) -> str: """ Tool to use the Virtuoso AI support function Args: prompt (str): AI prompt text (required). api_key (str): API key for AI service (optional). user (Optional[str]=None): Optional username. password (Optional[str]=None): Optional password. dsn (Optional[str]=None): Optional dsn name. Returns: str: Results data in JSON. """ try: _api_key = api_key if api_key is not None else API_KEY with get_connection(True, user, password, dsn) as conn: cursor = conn.cursor() cmd = f"select DEMO.DBA.OAI_VIRTUOSO_SUPPORT_AI(?, ?) as result" rs = cursor.execute(cmd, (prompt, _api_key,)).fetchone() return rs[0] except pyodbc.Error as e: logging.error(f"Error executing request") raise pyodbc.Error("Error executing request") - mcp_sqlalchemy_server/server.py:445-448 (registration)The @mcp.tool decorator registers the tool with name 'podbc_virtuoso_support_ai' and its description.
@mcp.tool( name="podbc_virtuoso_support_ai", description="Tool to use the Virtuoso AI support function" )