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672,397 tools. Updated 2026-10-18 08:42

"Understanding SQL Server Schema and Querying" matching MCP tools:

  • Retrieve the archive database schema, including table and column names. Understand available data for crafting SQL queries.
    Apache 2.0
  • Execute large market data API calls and optionally store results as in-memory DataFrames for SQL querying. Automatically detects pagination via _next_page to retrieve complete datasets.
    MIT
  • Remove a SQL schema from a Microsoft Fabric warehouse or SQL Analytics endpoint. Use cascade to permanently delete tables and views within the schema.
    MIT
  • Retrieve the schema, sample data, and row count of a parquet file to analyze its structure before querying. Ideal for understanding columns, data types, and preparing SQL queries efficiently.
    MIT
  • Move a T-SQL user-defined function to a different schema using ALTER SCHEMA TRANSFER. Supports Data Warehouses and SQL Analytics endpoints, without altering the function's stored definition.
    MIT

Matching MCP Servers

Matching MCP Connectors

  • SchemaOAuth

    The AI that understands raw data: Schema over your tables and databases, as MCP tools.

  • MCP server (stdio): validate JSON against JSON Schema (draft-07 / 2020-12) via the AgentForge API

  • Generate example SQL queries for blockchain datasets using DuckDB. Streamline querying and schema inspection for Ethereum data with workflow tips. Enhance efficiency in blockchain data analysis.
    MIT
  • Access the complete database schema, relationships, and SQL patterns to understand Shopify store data structure before querying.
    MIT
  • Execute SQL queries via Superset's SQL Lab to retrieve data. Provide database ID and SQL; set schema, catalog, or template params as needed.
    MIT
  • Retrieve the SQL definition and column structure of PostgreSQL views to understand database schema and query logic.
    MIT
  • Fetch historical stock price data and load it into a SQL database for analysis. Use this tool to prepare market data for SQL queries, enabling detailed financial analysis of price trends and patterns.
    MIT
  • Fetch option chain data and load it into an SQL database for analysis using SQL queries. This tool enables structured querying of options data for the specified underlying symbol.
    MIT
  • Run a read-only SQL SELECT/WITH statement on a SQLite database and receive the result rows as JSON. Inspect schema resources to understand tables and columns before querying.
    MIT
  • Get full object definitions from SAP Datasphere—table columns, view SQL, model measures, and data-flow transformations. Use it to understand implementation details or extract schema for migrations.
    MIT
  • List all tables in a Microsoft Fabric lakehouse. Falls back to querying INFORMATION_SCHEMA for schema-enabled lakehouses to ensure complete results.
    AGPL 3.0
  • Move an existing SQL view into a target schema on a Microsoft Fabric warehouse or SQL analytics endpoint while keeping its definition intact.
    MIT
  • List SQL tables in a Microsoft Fabric warehouse or SQL Analytics Endpoint, optionally filtering by schema to find tables quickly.
    MIT
  • Retrieve the full schema of an explore, listing all dimensions, measures, filters, and parameters available for querying.
    Apache 2.0