MsSqlMCP – A Model Context Protocol Server for SQL Server Schema Exploration

MsSqlMCP is an MCP server that empowers AI assistants to interrogate the schema of a Microsoft SQL Server database. By exposing the structure—tables, columns, data types, and relationships—to an AI client, it removes a major barrier for developers who want to embed intelligent database navigation and query generation directly into their IDE or workflow. Instead of manually consulting documentation or running ad‑hoc queries, a developer can ask an assistant to “list all foreign keys on the table” or “show me the columns in that are of type ”, and receive instant, reliable answers sourced from the live database.

The server runs as a lightweight .NET 9 application and communicates over standard I/O, making it trivial to launch from Visual Studio Code or any other MCP‑compatible client. Its core functionality is a set of declarative schema queries that the assistant can invoke via MCP prompts. These include retrieving table lists, column definitions, primary and foreign key constraints, and even relationship graphs. The assistant can then use this metadata to validate user input, auto‑complete SQL snippets, or generate documentation. Because the data is pulled directly from the database’s information schema, developers can trust that the assistant reflects the current state of their environment, even as tables are added or modified.

Key capabilities in plain language:

• Schema discovery – enumerate tables, views, and stored procedures with minimal effort.
• Column introspection – retrieve column names, data types, nullability, and default values.
• Relationship mapping – identify primary key/foreign key pairs and visualize how tables are linked.
• Contextual query help – feed schema data back to an assistant so it can suggest complete, syntactically correct queries or troubleshoot errors.

Real‑world use cases abound: a data engineer can let an assistant draft ETL scripts that reference the latest schema; a front‑end developer can quickly understand which columns are available for data binding; a database administrator can generate audit reports that list all tables lacking primary keys. In educational settings, students can experiment with AI‑guided SQL exploration without setting up a separate documentation portal.

Integration is straightforward. Once the MCP server is running, any AI client that supports MCP can declare a prompt like “Show all columns in the table” and receive a structured JSON response. The assistant can then embed this information into its reply, or use it to populate an autocomplete list in the editor. Because MsSqlMCP is built on .NET, it can run cross‑platform and be easily extended with custom logic if needed.

What sets MsSqlMCP apart is its focus on schema rather than query execution. While many tools provide raw SQL editors, this server gives the assistant a semantic understanding of the database, enabling higher‑level reasoning and smarter suggestions. For developers who rely on AI assistants to accelerate data‑centric workflows, MsSqlMCP delivers the precise context needed to make those assistants truly intelligent.