Execute parameterized SQL queries, persist large result sets as volatile tables, and retrieve up to 50,000 rows with truncated data notification.
MIT
160,878 tools. Last updated 2026-05-29 22:43
"SQLAlchemy" matching MCP tools:
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- Create a new database connection in Apache Superset by providing connection details like SQLAlchemy URI, engine type, and database name to enable data visualization.MIT
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Matching MCP Servers
- AlicenseCqualityDmaintenanceProvides SQLAlchemy (via pyodbc) connectivity to any Database Management System (DBMS) that's accessible via SQLAlchemy.Last updated1123MIT
- -license-quality-maintenanceA server for managing financial accounting entries that provides utilities for database access using SQLAlchemy with environment-based configuration.Last updated
- Execute SQL queries on Teradata databases using SQLAlchemy, returning results with rendered SQL metadata for analysis and management.MIT
- Retrieve detailed column information for Teradata database tables, including data types and constraints, with SQL query metadata returned.MIT
- Run SQL queries and retrieve results formatted as Markdown tables using SQLAlchemy connectivity, enabling easy integration with any DBMS.MIT
- Retrieve a list of all schema names from a connected database using SQLAlchemy via pyodbc, enabling efficient database schema management.MIT
- Retrieve the Data Definition Language (DDL) for a Teradata table to view its structure and schema definition. This tool displays the complete SQL statement used to create or alter the table.MIT
- Filter and retrieve table names containing a specific substring from any DBMS using SQLAlchemy connectivity via pyodbc, returning schema and table details in a structured list.MIT
- Retrieve a list of tables and their details from a specified database schema using SQLAlchemy connectivity. Automatically defaults to the connection schema if none is provided.MIT
- Execute SQL queries on any DBMS via SQLAlchemy connectivity and retrieve results in JSONL format for streamlined data processing.MIT
- Execute SPASQL queries on databases via SQLAlchemy connectivity, enabling retrieval of structured results with customizable row limits and timeout settings.MIT
- Execute SQL queries and retrieve results in JSONL format. Configure max rows, parameters, and connection URL for precise data extraction via SQLAlchemy connectivity.MIT
- Retrieve table definitions, including column names, data types, and keys, from any SQLAlchemy-accessible DBMS using the MCP server's pyodbc connectivity.MIT
- Preview data samples and table structure from Teradata databases to verify content and schema before analysis or querying.MIT
- Analyze table usage patterns to identify relationships between database tables, supporting SQL query generation and metadata extraction for Teradata databases.MIT
- Measure table and view usage by users in a Teradata schema to identify active database objects and their value through SQL analysis.MIT