MSSQL MCP Python Server

MSSQL MCP Python Server

MCP server for safely exposing SQL Server database capabilities to LLM clients, with read-only mode, security features, and observability.

Category
Visit Server

README

<div align="center"> <img src="docs/logo.png" alt="logo"> </div>

MSSQL MCP Python Server

GitHub stars GitHub forks GitHub issues Python Version GitHub release Downloads

This is a MCP (Model Context Protocol) server implementation in Python that safely exposes SQL Server database capabilities to LLM clients.

  • If you want a complete guide of how to use, click here!

Quick Start

1. Install Dependencies

cd mssql-mcp-python
pip install -r requirements.txt

# or:
uv sync

2. Configure Database

Create .env file:

# For local SQL Server (Linux/Docker)
export MSSQL_CONNECTION_STRING="Driver={ODBC Driver 17 for SQL Server};Server=localhost,1433;Database=master;UID=sa;PWD=YourPassword123"

# Or for Windows Auth
export MSSQL_CONNECTION_STRING="Driver={ODBC Driver 17 for SQL Server};Server=localhost;Database=master;Trusted_Connection=yes"

3. Run the Server

# With stdio transport (for MCP clients)
python -m mssql_mcp.cli

# With custom settings
MSSQL_QUERY_TIMEOUT=60 READ_ONLY=true python -m mssql_mcp.cli --log-level DEBUG

# Or with HTTP transport
python -m mssql_mcp.cli --transport http --bind 0.0.0.0:8080

# Build and run
docker build -t mssql-mcp:latest .
docker run -e MSSQL_CONNECTION_STRING="..." mssql-mcp:latest

4. Test with curl (HTTP mode)

# Health check
curl http://localhost:8080/health

# Readiness check
curl http://localhost:8080/ready

# Server info
curl http://localhost:8080/info

# Prometheus metrics
curl http://localhost:8080/metrics

Available MCP Tools

The server exposes these tools to MCP clients:

1. execute_sql(sql, format="table")

Execute SELECT queries (or write operations if enabled)

Input: "SELECT * FROM users LIMIT 10"
Output: ASCII table or JSON

2. list_schemas()

List all database schemas

Input: (none)
Output: Schema names list

3. list_tables(schema, limit=200)

List tables with optional schema filter

Input: schema="dbo", limit=100
Output: Table list with metadata

4. schema_discovery(schema)

Get full schema metadata (tables, columns, types)

Input: schema="dbo"
Output: JSON with detailed column info

5. get_database_info()

Get server/database metadata

Input: (none)
Output: Database name, version, machine name

6. get_policy_info()

Get current security policy settings

Input: (none)
Output: Policy details (allowed operations, limits)

7. check_db_connection()

Health check for database connectivity

Input: (none)
Output: Connection status

Security Features

✅ Read-Only by Default

  • Only SELECT queries allowed unless explicitly enabled
  • Writes require ENABLE_WRITES=true + ADMIN_CONFIRM token

✅ SQL Injection Prevention

  • Parameterized queries via pyodbc
  • Multi-statement query blocking
  • Banned keyword detection (DROP, ALTER, EXEC, etc.)

✅ Sensitive Data Protection

  • Automatic log redaction (passwords, connection strings)
  • Query hashing for safe logging
  • No credentials in response bodies

✅ Resource Limits

  • Query timeouts (default 30s)
  • Row limits (default 50,000 rows)
  • Query length limits (50KB)
  • Connection pool limits

✅ Audit Trail

  • Structured logging with request metadata
  • Query metrics and statistics
  • Client ID tracking (when provided)

Observability

Prometheus Metrics

Available at GET /metrics (HTTP mode):

  • mssql_queries_executed_total — Total queries by tool and status
  • mssql_queries_blocked_total — Blocked queries by reason
  • mssql_query_duration_seconds — Query latency histogram
  • mssql_query_rows_returned — Result set size histogram
  • mssql_active_queries — Currently executing queries
  • mssql_server_ready — Server readiness (0/1)

Structured Logs

All logs in JSON format (when LOG_FORMAT=json):

{
  "timestamp": "2024-01-15T10:30:00.123456",
  "level": "INFO",
  "logger": "mssql_mcp.tools",
  "message": "Query allowed",
  "module": "tools",
  "function": "execute_sql",
  "line": 42
}

Health Checks

  • GET /health — Liveness probe (always 200)
  • GET /ready — Readiness probe (200 if DB connected)

Common Tasks

Change Log Level

LOG_LEVEL=DEBUG python -m mssql_mcp.cli

Enable Write Operations

ENABLE_WRITES=true ADMIN_CONFIRM=secret python -m mssql_mcp.cli

Increase Query Timeout

MSSQL_QUERY_TIMEOUT=120 python -m mssql_mcp.cli

Run Multiple Instances

python -m mssql_mcp.cli --transport http --bind 127.0.0.1:8080
python -m mssql_mcp.cli --transport http --bind 127.0.0.1:8081  # Different port

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured