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SQL Server Agent

by aman-panjwani

Data/Access & IntegrationSQL ServerAI AgentModal Context ProtocolDatabase Query

The SQL Server Agent allows you to interact with SQL Server databases using natural language, leveraging the Modal Context Protocol (MCP). It acts as a smart layer between language models and the database, enabling no-code database operations.

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What is SQL Server Agent?

The SQL Server Agent is a conversational AI Query CLI that enables you to interact with your SQL Server Database using natural language. Powered by the Modal Context Protocol, it acts as a smart layer between your language model and the database, making it possible to query your database without writing SQL and execute stored procedures with conversational commands.

How to use SQL Server Agent?

  1. Clone the repository. 2. Install dependencies using pip install -r requirements.txt. 3. Setup environment variables in a .env file (OPENAI_API_KEY, MSSQL_SERVER, MSSQL_DATABASE, MSSQL_USERNAME, MSSQL_PASSWORD, MSSQL_DRIVER). 4. Run the client script using python mcp-ssms-client.py. 5. Enter your query in plain English when prompted.

Key features of SQL Server Agent

  • Talk to Your Database: Chat with SQL Server using plain English.

  • No-Code Database Operations: Manage your database tasks entirely through natural conversations.

  • One-Click Procedure Execution: Run stored procedures effortlessly with natural commands.

  • MCP-Enhanced Accuracy: Achieve precise database interactions through Modal Context Protocol (MCP), intelligently connecting your commands to data.

  • Context-Aware Conversations: Enjoy seamless interactions powered by Modal Context Protocol.

Use cases of SQL Server Agent

  • Querying databases without writing SQL.

  • Executing stored procedures with conversational commands.

  • Performing complex database operations while maintaining context.

  • Making database access more intuitive for non-technical users.

FAQ from SQL Server Agent

What is MCP?

MCP (Modal Context Protocol) is a methodology that states how we should bind the context to the LLMs. MCP provides a standardized way to connect AI models to different data sources and tools.

Why use MCP?

MCP helps us to build complex workflows in a simplified way to build Agents on top of LLMs where the language models needs a frequent integration with the data sources and tools.

What are the prerequisites?

You need Python 3.12+ and a valid OpenAI API Key.

How do I install the dependencies?

Run pip install -r requirements.txt after cloning the repository.

How do I run the SQL Server Agent?

Execute the command python mcp-ssms-client.py after setting up the environment variables.