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"Techniques for Analyzing and Interacting with Large MS SQL Databases" matching MCP servers:

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  • F
    license
    Not graded
    quality
    C
    maintenance
    Enables LLMs and agents to interact with relational databases (SQL Server, MySQL, PostgreSQL) through MCP tools. Supports executing queries, inserting records, listing tables, and exposing database schemas with secure credential management.
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  • A
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    quality
    D
    maintenance
    Enables AI to interact with Microsoft Access (.mdb, .accdb) and SQLite 3 databases, including read-only support for Access 97 databases. Supports executing SQL queries, importing/export data from CSV and Excel files, and storing notes about database files.
    MIT
  • F
    license
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    quality
    D
    maintenance
    Enables AI assistants to interact with SQL Server databases through tools for connectivity, schema exploration, SQL queries, and OEE metrics analysis.
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  • A
    license
    B
    quality
    C
    maintenance
    Enables AI agents to interact with Microsoft Fabric by exposing tools for managing workspaces, notebooks, SQL queries, pipelines, and Livy Spark sessions. It provides a comprehensive set of operations for data engineering and analytics tasks using standard Azure authentication.
    37
    4
    MIT
  • A
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    quality
    C
    maintenance
    Executes SQL queries via ConnectorX and streams results to CSV or Parquet files, supporting multiple databases and optional token counting for CSV output.
    1
    MIT
  • A
    license
    A
    quality
    A
    maintenance
    50 tools and 400 functions for working with Excel/.xlsx spreadsheets — read/write, recalculate formulas, diff, repair broken references, and audit. Built for AI agents.
    50
    3,303 npm
    6
    MIT
  • A
    license
    Not graded
    quality
    C
    maintenance
    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.
    15 npm
    MIT
  • A
    license
    Not graded
    quality
    A
    maintenance
    A fast, safe MCP server for YNAB providing read-only budget access by default, with 28 tools for budgets, transactions, categories, payees, accounts, scheduled transactions, and server-computed analytics.
    MIT
  • A
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    Not graded
    quality
    D
    maintenance
    MCP server that connects AI assistants to Redash, enabling listing of assets, read-only query execution, dashboard inspection, and alert management through the Redash API.
    MIT
  • A
    license
    Not graded
    quality
    D
    maintenance
    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.
    5
    MIT
  • A
    license
    Not graded
    quality
    C
    maintenance
    A Windows-optimized server providing universal data analytics for JSON and CSV files through over 32 tools including schema discovery and interactive visualizations. It is specifically designed for seamless integration with Claude Desktop on Windows.
    1
    MIT
  • A
    license
    Not graded
    quality
    D
    maintenance
    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.
    0
    ISC
  • F
    license
    C
    quality
    D
    maintenance
    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.
    83
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  • A
    license
    Not graded
    quality
    C
    maintenance
    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.
    Apache 2.0
  • A
    license
    Not graded
    quality
    C
    maintenance
    Exposes a synthetic issue tracker and pipeline warehouse as callable tools so an agent can answer operational questions about tickets, pipeline health, runs, incidents, and governed metrics with every claim cited to the exact tool call it came from. All writes are proposal-only, requiring human approval through a gated apply path that logs each step for audit.
    MIT