Retrieve official step-by-step instructions to instrument Scout APM for your framework, supporting web, background jobs, and database libraries.
MIT
337,767 tools. Last updated 2026-07-30 03:22
"SQLAlchemy" matching MCP tools:
- 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
- Configure a new database source in the configuration file, including optional connection testing. Supports SQL Server and Snowflake via linked server.GPL 3.0
- Generate SQLAlchemy 2.0 declarative models from a PostgreSQL schema, covering columns, primary/foreign keys, constraints, defaults, and enums.MIT
- Turn any database schema into a Mermaid ER diagram. Accepts SQL DDL, Prisma, Drizzle, TypeORM, or SQLAlchemy schemas.MIT
- Scan a Python project for patterns that may break obfuscation, such as eval/exec or dynamic attribute access. Returns severity counts, detected frameworks, and a suggested preset.Apache 2.0
Matching MCP Servers
- AlicenseCqualityFmaintenanceProvides SQLAlchemy (via pyodbc) connectivity to any Database Management System (DBMS) that's accessible via SQLAlchemy.Last updated1124MIT
- -license-quality-maintenanceA server for managing financial accounting entries that provides utilities for database access using SQLAlchemy with environment-based configuration.Last updated
- Add a field to any model, class, or interface in Prisma, Python, or TypeScript files. Specify model name, field name, and type.MIT
- Create a new project with any supported framework such as Spring Boot, React, Vue, Next.js, FastAPI, and others. Configure options including TypeScript, testing, Docker, and database.MIT
- Execute SQL queries with optional parameter binding to retrieve data from Teradata databases, returning query results and metadata.MIT
- Preview a Teradata table or view to retrieve a data sample, inferred column structure, and the rendered SQL query.MIT
- Identify tables frequently used together in database queries to infer relationships between database objects. Returns fully rendered SQL with metadata.MIT
- Retrieve detailed column information for Teradata database tables, including data types and constraints, with SQL query metadata returned.MIT
- Execute SQL queries on Teradata databases using SQLAlchemy, returning results with rendered SQL metadata for analysis and management.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
- 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 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
- Show column names, data types, and metadata for a Teradata database table or view.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 and retrieve results in JSONL format. Configure max rows, parameters, and connection URL for precise data extraction via SQLAlchemy connectivity.MIT