"SQL Queries for Snowflake Database Administration" matching MCP servers:

Enables execution of Snowflake stored procedures through the MCP server by providing a framework to define, manage, and call procedures from specific schemas or individual procedures.

Enables LLM agents to explore and query a Postgres database through secure, read-only tools.

An MCP server that lets Claude query a mock business SQL database in plain language through read-only tools, with server-side guardrails that enforce SELECT-only queries and block access to sensitive payment data.

An MCP server that connects LLMs to SQL databases for development assistance, enabling query execution, schema exploration, and data manipulation while providing safety controls against destructive operations.

An extensible MCP server for database operations that supports PostgreSQL for managing schemas, tables, data, and user permissions. It features automatic migration recording for DDL changes and integrates with various AI-powered editors like Cursor, Zed, and Claude Code.

Enables Large Language Models to access and manipulate Autodesk Revit models through a pyRevit-based bridge and the Model Context Protocol.

MCP server for snowflake that doesn't allow write operations under any circumstances, and includes a system prompt.

A Model Context Protocol server that allows Large Language Models like Claude to execute SQL queries, explore database schemas, and maintain persistent connections to SQL Server databases.

Gives LLM agents spatial awareness inside Autodesk Maya, enabling scene inspection and measurement, aesthetic and engineering audits, camera planning, checkpoint/rollback safety, asset import, and viewport or render previews. Agents can also execute arbitrary Python in Maya to build and verify 3D scenes against engineering rules instead of writing blind.

Enables AI agents to invoke a local Stata installation, including a Windows Stata build under Wine on Linux and macOS, for regression analysis, econometrics, paper replication, and empirical research with command guards, resource monitoring, and automatic log capture.

A TypeScript-based MCP server that enables LLM agents to interact with Gel databases through natural language, providing tools to learn database schemas, validate and execute EdgeQL queries.

Gives AI assistants full control over Microsoft Access databases, enabling creation and management of forms, VBA, tables, queries, and more through natural language.

Enable Claude (or any other LLM) to interactively debug your code (set breakpoints and evaluate expressions in stack frame). It's language-agnostic, assuming debugger console support and valid launch.json for debugging in VSCode.

A server that helps people access and query data in databases using the Query Runner with integration of the Model Context Protocol (MCP) Python SDK. Support databases including PostgreSQL Redshift MySQL Microsoft SQL Server Google APIs Amazon Web Services (via boto3) CockroachDB SQLite

A Model Context Protocol server implementation that provides a simple interface to interact with PostgreSQL databases, enabling SQL queries, database operations, and schema management through MCP.

A FastMCP server that enables natural language querying of PostgreSQL databases through LLM integration, allowing users to generate SQL queries from plain English and visualize the results.

MCP server that gives AI agents isolated, named Linux computers with stable IDs and lifecycle control. Supports multiple backends like Docker, Fly Machines, Modal, and E2B, with a dashboard for managing sandboxes.

Enables MCP clients such as Claude Desktop or Cursor to inspect a coffee-shop sales database schema, validate SQL, and run guarded read-only queries. It supports natural-language questions by exposing tools for schema description, SQL checking, and safe query execution.

Facilitates interaction with Microsoft SQL Server Express, supporting database operations such as querying, table management, and schema inspection via natural language MCP commands.

Enables LLMs to drive Blender through socket-based two-way communication, letting them create and modify 3D objects, apply materials, run Blender Python, and fetch or generate assets while visually verifying results. Supports prompt-assisted 3D modeling, scene creation, and manipulation.