Frequently Asked Questions (FAQ) about MCP SQL Server

Q: What is MCP SQL Server?

A: MCP SQL Server is a Model Context Protocol (MCP) server that provides comprehensive access to SQL databases, primarily MSSQL, for AI assistants. It enables AI agents to inspect database schemas, execute queries, and perform database operations securely.

Q: What databases are currently supported?

A: Currently, MCP SQL Server fully supports Microsoft SQL Server (MSSQL). Support for MySQL and PostgreSQL is planned for future releases.

Q: What is MCP (Model Context Protocol)?

A: MCP is an open protocol that standardizes how applications provide context to Large Language Models (LLMs). It acts as a bridge, allowing AI models to access and interact with external data sources and tools.

Q: How does MCP SQL Server enhance security?

A: MCP SQL Server incorporates several security measures, including SQL injection prevention through parameterized queries, connection encryption (TLS/SSL), access controls based on database user permissions, and comprehensive query execution logging.

Q: What AI assistants are compatible with MCP SQL Server?

A: MCP SQL Server natively supports Claude Desktop, Cursor, and any MCP-compatible tools.

Q: How do I install MCP SQL Server?

A: You can install MCP SQL Server globally using npm with the command: npm install -g @donggyunryu/mcp-sql.

Q: What are the prerequisites for using MCP SQL Server?

A: The prerequisites include Node.js 18.0.0 or higher, a Microsoft SQL Server (MSSQL) instance, and an MCP-compatible AI assistant such as Claude Desktop or Cursor.

Q: How do I configure MCP SQL Server?

A: Configuration involves creating a .env file with your database connection details (host, port, database name, username, password, etc.) and then configuring your AI assistant to use the MCP SQL Server by adding the server’s configuration to your assistant’s settings file.

Q: What tools are available for database interaction?

A: The server provides tools for schema discovery (e.g., list_tables, describe_table, get_schema), query execution (execute_query, start_batch_processing), and performance monitoring (get_connection_pool_status, get_query_stats, generate_performance_report).

Q: Can I use MCP SQL Server to automate database tasks?

A: Yes, MCP SQL Server enables you to automate routine database tasks by configuring AI agents to proactively identify and address potential issues, minimize downtime, and ensure optimal database performance.

Q: What is the UBOS platform, and how does it relate to MCP SQL Server?

A: UBOS is a full-stack AI Agent Development Platform that allows to orchestrate AI Agents, connect them with your enterprise data, build custom AI Agents with your LLM model and Multi-Agent Systems. MCP SQL Server is an asset within the UBOS marketplace that allows AI Agents to interact with SQL server databases.

Q: Is there a roadmap for future development?

A: Yes, the roadmap includes plans for multi-database support (MySQL, PostgreSQL), performance enhancements, improved testing and quality assurance, advanced features like GraphQL integration, and enhanced analytics and insights.

Q: Where can I report issues or request features?

A: You can report bugs or request features on the project’s GitHub repository in the Issues section.

Q: What license is MCP SQL Server released under?

A: This project is licensed under the MIT License. See the LICENSE file for details.