"Information about Microsoft SQL Server" matching MCP servers:

Enables AI assistants to interact with Microsoft Fabric and Power BI services through the Model Context Protocol. Users can manage workspaces, execute DAX queries, refresh datasets, and create Fabric notebooks using natural language.

Provides read-only Microsoft SQL Server database access to AI agents with row-level security, enabling SELECT queries, table metadata, and schema introspection through MCP.

Enables AI assistants to interact with SQL Server databases through tools for connectivity, schema exploration, SQL queries, and OEE metrics analysis.

Enables secure interaction with multiple SQL database engines (MySQL, PostgreSQL, SQLite, SQL Server) through a standardized interface. Supports schema inspection, safe query execution, and controlled write operations with built-in security restrictions.

A Model Context Protocol server that lets you fetch Microsoft Clarity analytics data through Claude for Desktop or other MCP-compatible clients, with support for filtering by dimensions and retrieving various metrics.

A Python MCP server that lets you manage Microsoft Fabric through natural language in Claude Code or Claude Desktop, with 77+ tools covering workspaces, lakehouses, warehouses, SQL, DAX, semantic models, notebooks, pipelines, OneLake, and Microsoft Graph.

A read-only Model Context Protocol server for Microsoft Fabric, enabling natural language queries to workspaces, lakehouses, tables, jobs, and dependencies.

Exposes Microsoft Fabric operations as MCP tools, with 105 tools across 17 domains including lakehouses, warehouses, notebooks, pipelines, and real-time analytics, handling long-running operations and supporting multiple authentication modes.

A metadata-guided, read-only SQL analysis MCP server for DataHub that helps agents perform safe analytical queries using DataHub schema, lineage, ownership, and tags, with a deterministic planner and strict SQL safety layer against local synthetic SQLite, guaranteeing zero write or mutation operations.

An AI-driven data visualization and SQL chat platform that enables natural language to SQL conversion, interactive chart generation, and database querying through a comprehensive MCP interface. Supports multiple databases, intelligent chart recommendations, and secure data management with temporary link sharing.

Bridges Microsoft Clarity's analytics API with Claude, enabling custom date ranges and page-level filtering on top of Clarity's native limitations.

A read-only MCP server for querying SQL Server Analysis Services (multidimensional cubes via MDX and tabular models via DAX) using Windows Integrated Security.

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

An MCP server that provides safe, read-only access to a PostgreSQL warehouse, enabling schema introspection, guarded SQL queries, and truncated result reporting for LLMs.

Enables LLM agents to query governed GA4 metrics over MCP, returning definitions, assumptions, and failure modes from a MetricFlow semantic layer without writing SQL.

Provides a stateful local Spark session for running PySpark and SQL cells, enabling local data exploration before deploying to Microsoft Fabric.

A tool that converts natural-language requests into full, deployable, execution-verified Apache Flink SQL jobs by orchestrating an LLM to draft specs, generate Flink SQL, and verify correctness against real Flink clusters and streaming semantics—including windowed aggregates, joins, Kafka grounding, and Deployable pipelines via the generate_flink_job, ground_kafka_topic, and deploy_to_kafka tools.

Bridges Microsoft Foundry agents and Power BI semantic models into GitHub Copilot Chat, enabling users to query and modify measures as the signed-in user via MCP.

Enables AI assistants to interact with Hadoop Hue for executing SQL queries using Hive, SparkSQL, or Impala and managing HDFS files. It supports directory browsing, file transfers, and exporting query results to CSV through the Model Context Protocol.

Enables executing SQL queries, exploring database schemas, and exporting results from Redash via MCP, with ad-hoc queries and write protection.