Skip to main content
Glama
DhruviPatel712

SJSINGLE_AI SQL Server MCP

SJSINGLE_AI SQL Server MCP

Production-ready Model Context Protocol server for Microsoft SQL Server, configured for the SJSINGLE_AI database.

Features

  • SQL Server MCP tools for schema discovery and safe read-only queries

  • SJSINGLE_AI configured as the default database

  • Optional multi-database catalog through databases.json

  • Read-only by default, with DDL/admin commands blocked

  • Row limits and query timeout controls

  • Live schema metadata discovery

  • LangChain-powered natural-language read-only SQL tool

  • stdio transport for Cursor and optional streamable HTTP transport

Related MCP server: mssql-mcp-server-python

Setup

cd D:\DHRUVI_MCP_SERVER\DHRUVI_MCP_SERVER
copy .env.example .env

Edit .env and set the real SQL Server password:

MSSQL_SERVER=4.240.84.65
MSSQL_PORT=1433
MSSQL_DATABASE=SJSINGLE_AI
MSSQL_DATABASES=SJSINGLE_AI
MSSQL_USER=sjreadonly
MSSQL_PASSWORD=your-secure-password
MSSQL_MAX_ROWS=10
AZURE_OPENAI_ENDPOINT=https://your-resource-name.openai.azure.com/
AZURE_OPENAI_DEPLOYMENT=your-foundry-model-deployment-name
AZURE_OPENAI_API_KEY=your-azure-openai-key
AZURE_OPENAI_API_VERSION=2024-10-21

Install dependencies:

.\.venv\Scripts\python.exe -m pip install -e ".[dev]"

Run tests:

.\.venv\Scripts\python.exe -m pytest

Start the MCP server:

.\.venv\Scripts\python.exe -m sqlserver_mcp

For HTTP mode, keep these values in .env:

MCP_TRANSPORT=streamable-http
MCP_HTTP_HOST=127.0.0.1
MCP_HTTP_PORT=8765

Then start the same command. The endpoint is:

http://127.0.0.1:8765/mcp

Cursor MCP

Use mcp.json.example as the Cursor MCP configuration template. It points at this folder and starts:

.\.venv\Scripts\python.exe -m sqlserver_mcp

Keep PYTHONPATH=D:\DHRUVI_MCP_SERVER\DHRUVI_MCP_SERVER\src in the MCP environment so Cursor loads the current source files, not an older installed package.

Runtime MCP instructions are passed inline from src/sqlserver_mcp/server.py through FastMCP. AGENT_INSTRUCTIONS.md is kept as human-readable documentation and does not need to be loaded into the MCP runtime.

Main tools:

  • list_databases

  • list_schemas

  • list_tables

  • describe_table

  • search_objects

  • table_column_counts

  • recommend_business_view

  • get_stone_detail

  • execute_query

  • execute_parameterized_query

  • answer_question_with_langchain

  • get_database_info

Safety

The server is read-only unless MSSQL_ALLOW_WRITE=true. Even then, destructive/admin SQL such as DROP, ALTER, CREATE, EXEC, TRUNCATE, BACKUP, and DBCC remains blocked.

LangChain

answer_question_with_langchain uses LangChain to generate one read-only T-SQL query from a natural-language question. The generated query is still executed through the MCP server's normal SQL validator and row cap.

Business questions are routed to preferred MCP views before SQL generation:

  • Stone detail, stock, inventory, packet, or diamond questions: MCP.VIEW_STOCK_STONE_DATA

  • Party eBid, bid, bidding, auction, or eBid result questions: MCP.VIEW_EBID_RESULT_DETAILS_DATA

  • Party, party detail, customer profile, customer expression, interest, or preference questions: MCP.VIEW_CUSTOMER_PROFILE_DATA and MCP.VIEW_CUSTOMER_EXPRESSION_DATA

  • Website activity, last activity, user tracking, page visit, or login activity questions: MCP.VIEW_USER_TRACKING_LOG_DATA

Preferred input columns:

  • MCP.VIEW_CUSTOMER_EXPRESSION_DATA: PARTY_COMPANY_NAME

  • MCP.VIEW_CUSTOMER_PROFILE_DATA: WEB_USER_NAME or COMPANY_NAME

  • MCP.VIEW_SALES_STONE_DATA: SERIAL_NO

  • MCP.VIEW_STOCK_STONE_DATA: SerialNo or COMPANY_NAME

  • MCP.VIEW_USER_TRACKING_LOG_DATA: COMPANY_NAME

  • MCP.VIEW_EBID_RESULT_DETAILS_DATA: PARTY_COMPANY_NAME

Query responses are capped at 10 rows.

For a direct stock stone serial lookup, use get_stone_detail(serial_no="533007"). It performs one query against [MCP].[VIEW_STOCK_STONE_DATA] with a SerialNo filter.

Equivalent direct SQL:

SELECT TOP (1) * FROM [MCP].[VIEW_STOCK_STONE_DATA] WHERE [SerialNo] = SerialNo

For more than one serial, use IN and do not add TOP (10):

SELECT * FROM [MCP].[VIEW_STOCK_STONE_DATA] WHERE [SerialNo] IN (SerialNo1, SerialNo2)

For highest stock cost, calculate cost as GRATE * CARAT:

SELECT TOP (1)
    [SERIAL_NO],
    [STONE_ID],
    [GRATE],
    [CARAT],
    ([GRATE] * [CARAT]) AS [CalculatedCost]
FROM [MCP].[VIEW_STOCK_STONE_DATA]
ORDER BY ([GRATE] * [CARAT]) DESC

For highest sale discount, run the direct sales view query once:

SELECT TOP 1 * FROM [MCP].[VIEW_SALES_STONE_DATA] ORDER BY [discount] DESC

Configure:

# Azure AI Foundry / Azure OpenAI
AZURE_OPENAI_ENDPOINT=https://your-resource-name.openai.azure.com/
AZURE_OPENAI_DEPLOYMENT=your-foundry-model-deployment-name
AZURE_OPENAI_API_KEY=your-azure-openai-key
AZURE_OPENAI_API_VERSION=2024-10-21

LANGCHAIN_MODEL=gpt-4o-mini
LANGCHAIN_TEMPERATURE=0
LANGCHAIN_SCHEMA_TABLE_LIMIT=30
LANGCHAIN_INCLUDE_SQL=false

Schema discovery tools read live metadata from SQL Server on each call.

A
license - permissive license
-
quality - not tested
C
maintenance

Maintenance

Maintainers
Response time
Release cycle
Releases (12mo)
Commit activity

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/DhruviPatel712/dhruvi_mcp_server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server