"How to query data in Snowflake" 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.

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

Local MCP server that registers restricted Python filters and runs them against local JSON, YAML, and TXT files, enabling safe data filtering and file conversion.

Context Mode is an MCP server that reduces context window waste by sandboxing data-heavy tools, tracking session state in SQLite, and promoting code-based analysis over raw data reads, achieving up to 98% context savings.

Enables analysis of bulk RNA-seq data using natural language queries, executing R and Python in a Docker container with automatic sample anonymization and privacy controls.

Enables AI agents to dynamically register and query MySQL-compatible databases at runtime with built-in destructive SQL protection.

A demonstration server that reveals security risks by accessing sensitive environment variables, illustrating how MCP tools can potentially leak user data without explicit consent.

Allows LLMs to execute Python code in a specified Conda environment, enabling access to necessary libraries and dependencies for efficient code execution.

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.

Enables MCP-compatible AI agents to access Polymarket prediction-market data and run Python 3.12 in an isolated sandbox, with each call paid automatically in USDC on Base.

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.

A local MCP server that exposes Bazel build system functionality to AI agents, allowing them to build, test, query, and manage Bazel projects through natural language even in environments where Bazel can't be directly accessed.

MCP Server for the Peacock extension for VS Code (https://peacockcode.dev), coloring your world, one Code editor at a time. The main goal of the project is to show how an MCP server can be used to interact with APIs.

Enables Claude to generate executable test cases from decision tables in CSV, JSON, or Markdown formats. Provides intelligent test planning guidance and generates Playwright/API test code with TypeScript support.

A Model Context Protocol server that enables natural language interaction with Snowflake databases through AI guidance, supporting core database operations, warehouse management, and AI-powered data analysis features.

Enables AI assistants to inspect, refactor, lint, run, and version Power Query (M) queries in Excel workbooks and Power BI projects, with snapshot safety and live evaluation.

The Fibery MCP server provides integration between Fibery and any LLM provider supporting the MCP protocol (e.g., Claude for Desktop), allowing you to explore Fibery Workspace Schema, query databases, create and update entities using natural language.

An educational implementation of a Model Context Protocol server that demonstrates how to build a functional MCP server for integrating with various LLM clients like Claude Desktop.

Enables execution of Go code in the Go Playground sandbox and generation of shareable URLs for code snippets. Provides tools to run Go code, share code via URLs, or perform both operations simultaneously.

Exposes TypeScript Language Server Protocol functionality to AI agents, enabling them to query types at specific positions, find definitions and references, get diagnostics, run type tests, and type-check inline code just like in an IDE.