"Semantic layer for SQL query execution with dimensions and measures" matching MCP servers:

MCP server for the OrionBelt Semantic Layer. Enables LLMs to explore governed semantic models, compile YAML metric definitions into optimized SQL across 8 engines (BigQuery, ClickHouse, Databricks, Dremio, DuckDB, MySQL, PostgreSQL, Snowflake), and execute analytics queries via natural language. Works with Claude, Cursor, Windsurf, and Copilot.

A general-purpose MCP server that lets AI work with multiple databases within clear boundaries.

A server that enables querying the dbt Semantic Layer through natural language conversations with Claude Desktop and other AI assistants, allowing users to discover metrics, create queries, analyze data, and visualize results.

Analyzes SQL queries for performance issues, provides optimization suggestions with automated rewriting, and recommends indexes across multiple database dialects (PostgreSQL, MySQL, Oracle, SQL Server).

Exposes a governed semantic layer to AI agents so they select metrics and dimensions from a closed, engineer-declared vocabulary instead of writing SQL. Validates every typed call against the contract, rejects out-of-contract requests with structured errors and suggestions, and returns query rows together with the compiled SQL and dbt lineage for auditing.

Enables AI agents to read and optionally write to PostgreSQL databases through a multi-project setup with schema inspection, query execution, and performance analysis tools.

A governed SQL gateway that exposes typed tools to AI agents, compiling safe read-only queries from a semantic layer while blocking PII before execution, supporting SQL Server, Postgres, and SQLite.

A local MCP server for secure database querying from Claude Code, with Apple Keychain credential storage, permission-based access control, and audit logging.

Provides a semantic intelligence layer for SQL Server databases, enabling AI agents to understand schema structure, relationships, and safely interact through policy-gated tools.

A Model Context Protocol server that provides AI assistants with comprehensive access to SQL databases, enabling schema inspection, query execution, and database operations with enterprise-grade security.

A Model Context Protocol server for interacting with MSSQL and PostgreSQL databases, offering tools for schema exploration and SQL execution. It features configurable query modes for safety and supports advanced authentication methods like Windows Auth and SSL.

Enables read-only interaction with SQL databases through MCP, providing database metadata exploration, sample data retrieval, and secure query execution. Supports MySQL with multiple transport options and built-in security features including SQL injection protection and data sanitization.

NestJS-based MCP server for MySQL with session-level database selection and SQL safety controls. Enables executing SQL queries, listing databases, and connecting MySQL users with configurable safe modes.

Exposes a semantic layer on GA4 event data in BigQuery via an MCP server for consistent querying.

Enables natural-language sales queries against a SQLite database, generating and executing read-only SQL through a secure MCP server with table listing, schema description, and query execution.

Provides secure, read-only access to Microsoft SQL Server with multi-layer protection, enabling safe query execution, schema discovery, and SQL script analysis through natural language.

An MCP server that gives models semantic context about a data warehouse, including table meaning, units, lineage, and health, to reduce guessing.

Enables natural-language querying and analysis of an e-commerce SQLite database via MCP, with read-only SQL execution, table inspection, and AI-generated answers.

Enables MCP clients such as GitHub Copilot, Codex, Claude... to explore a SQL Server 2017+ database read-only: databases, schemas, tables, views, procedures, functions, indexes and dependency graphs, plus filtered, grouped, sampled and paginated queries capped by row limits.

Enables agents to query governed metrics through MCP, including describing metrics, running deterministic SQL against a warehouse, explaining join path preferences, and searching semantically ambiguous terms.