"Using GitLab Semantic Search for Code Implementation" matching MCP servers:

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.

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

A read-only PostgreSQL MCP server for AI coding agents that exposes database schema and sample data as tools, with LLM-powered semantic search enriched by a user-authored semantic layer.

Enables AI-assisted analysis and optimization of Cloudflare D1 databases through comprehensive schema introspection, relationship mapping, validation, and optimization recommendations. Demonstrates semantic intent patterns with hexagonal architecture for maintainable database development workflows.

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

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.

Enables AI agents to query verified-emissions knowledge graphs in natural language and validate data against supported standards, with metered billing and optional verified identity.

MCP server for Cloudflare D1 database introspection, providing schema analysis, relationship extraction, validation, and optimization suggestions via Semantic Intent patterns.

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.

MCP server for connecting to Microsoft Fabric and Power BI semantic models, enabling workspace browsing, dataset management, TMSL retrieval, DAX queries, model creation/editing, and includes a Best Practice Analyzer with 71 rules.

An MCP server that provides governed metric definitions and provenance-labeled memory for materials test labs, enforcing quality system discipline on agent interactions.

A server that enables document searching using Vertex AI with Gemini grounding, improving search results by grounding responses in private data stored in Vertex AI Datastore.

Builds rich code graphs from TypeScript/NestJS codebases using AST analysis and Neo4j, enabling semantic search, natural language querying, and intelligent graph traversal to provide deep contextual understanding of code relationships and dependencies.

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.

Model Context Protocol (MCP) server that gives AI assistants a safe, correct data-analyst capability over business metrics - without raw SQL improvisation.

Enables full-text search of macOS iMessages including link preview metadata. Works as an MCP server for Claude Desktop to search your messages locally.

Downloads your entire Search Console dataset into a local SQLite database, then gives your LLM a pre-built SQL query library for every standard SEO analysis type, with context available for your LLM to perform any SQL query to answer your questions and analyse for you.

Enables exploring Microsoft Fabric / Power BI workspaces and semantic models, and executing ad-hoc DAX queries.

Enables AI systems to perform full-text and semantic search operations over structured/unstructured data in Azure Cognitive Search, with capabilities for document indexing and management through natural language.

Provides access to Naver Search APIs, allowing AI agents to search across multiple categories (blogs, news, books, images, shopping items, etc.) with structured responses optimized for LLM consumption.