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608,788 tools. Updated 2026-09-25 05:31
"SQLAlchemy" matching MCP tools:
- Scan Python code for patterns that break obfuscation, get risk counts, frameworks detected, and a suggested preset. Optionally verifies dependencies against PyPI to catch hallucinated package names.Apache 2.0
- Diagnose slow Python/SQLAlchemy jobs by running them and getting the exact call site, query count, and fix, with optional per-unit trend analysis.MIT
- Create a new database connection in Apache Superset with a name and SQLAlchemy URI, enabling SQL Lab exposure, CTAS, CVAS, DML, and async queries.MIT
- 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
- Update a database connection in Apache Superset selectively. Confirm URI changes to prevent breaking datasets and charts.MIT
Matching MCP Servers
- AlicenseCqualityFmaintenanceProvides SQLAlchemy (via pyodbc) connectivity to any Database Management System (DBMS) that's accessible via SQLAlchemy.1124MIT
- -licenseNot gradedqualityNot gradedmaintenanceA server for managing financial accounting entries that provides utilities for database access using SQLAlchemy with environment-based configuration.-
- Establish a pooled connection to a database to enable subsequent operations, returning a connection ID. Choose a named configuration or direct SQLAlchemy URL.MIT
- Detect N+1 query patterns in SQLAlchemy by monitoring lazy loads. Identify relationships that trigger extra queries per row.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
- Read a PostgreSQL schema and output a SQLAlchemy 2.0 declarative models file with mapped columns, foreign keys, constraints, defaults, and enum classes.MIT
- Test a database connection by validating a SQLAlchemy URI without creating it. Ensure the URI is reachable from the Superset server to prevent setup issues.MIT
- Turn any database schema into a Mermaid ER diagram. Accepts SQL DDL, Prisma, Drizzle, TypeORM, or SQLAlchemy schemas.MIT
- Extract and document database models from a code repository, listing tables, fields, types, and relationships across SQLAlchemy, Django ORM, Prisma, TypeORM, and Mongoose.MIT
- Trace the full dependency chain from a frontend component through API routes to the corresponding SQLAlchemy database model.MIT
- Extract entities, fields, and relations from ORM models and database schemas to produce a readable data model for your business overview.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
- Identify field mismatches between SQLAlchemy ORM models and Pydantic schemas by comparing specified files and models, revealing discrepancies that cause validation or serialization errors.MIT
- Retrieve stack health diagnostics, graph statistics, and verification metrics for a repository to identify issues across React, FastAPI, and SQLAlchemy layers.MIT
- Execute SQL queries on Teradata databases using SQLAlchemy, returning results with rendered SQL metadata for analysis and management.MIT
- Execute SQL queries with optional parameter binding to retrieve data from Teradata databases, returning query results and metadata.MIT
- Preview data samples and table structure from Teradata databases to verify content and schema before analysis or querying.MIT