MSSQL MCP Server
MSSQL MCP 서버
Microsoft SQL Server 데이터베이스에 연결하기 위한 모델 컨텍스트 프로토콜(MCP) 서버입니다. 이 서버는 SQL 쿼리 실행 및 데이터베이스 연결 관리 도구를 제공합니다.
설치
Smithery를 통해 설치
Smithery를 통해 Claude Desktop용 MSSQL 데이터베이스 커넥터를 자동으로 설치하려면:
지엑스피1
수동 설치
npm install mssql-mcp-serverRelated MCP server: SQL MCP Server
용법
MCP 설정 구성 파일에 서버를 추가합니다.
{
"mcpServers": {
"mssql": {
"command": "mssql-mcp-server",
"env": {
"MSSQL_CONNECTION_STRING": "Server=localhost;Database=master;User Id=sa;Password=yourpassword;",
// Or individual connection parameters:
"MSSQL_HOST": "localhost",
"MSSQL_PORT": "1433",
"MSSQL_DATABASE": "master",
"MSSQL_USER": "sa",
"MSSQL_PASSWORD": "yourpassword",
"MSSQL_ENCRYPT": "false",
"MSSQL_TRUST_SERVER_CERTIFICATE": "true"
}
}
}
}도구
질문
MSSQL 데이터베이스에서 SQL 쿼리를 실행합니다.
매개변수
connectionString(문자열, 선택 사항): 전체 연결 문자열(개별 매개변수에 대한 대안)host(문자열, 선택 사항): 데이터베이스 서버 호스트 이름port(숫자, 선택): 데이터베이스 서버 포트(기본값: 1433)database(문자열, 선택 사항): 데이터베이스 이름(기본값: master)username(문자열, 선택 사항): 데이터베이스 사용자 이름password(문자열, 선택 사항): 데이터베이스 비밀번호query(문자열, 필수): 실행할 SQL 쿼리encrypt(부울, 선택 사항): 암호화를 활성화합니다(기본값: false)trustServerCertificate(부울, 선택 사항): 신뢰 서버 인증서(기본값: true)
connectionString 또는 ( host + username + password )를 제공해야 합니다.
예
const result = await use_mcp_tool({
server_name: 'mssql',
tool_name: 'query',
arguments: {
host: 'localhost',
username: 'sa',
password: 'yourpassword',
query: 'SELECT * FROM Users',
},
});개발
# Install dependencies
npm install
# Run in development mode
npm run dev
# Build
npm run build
# Run tests
npm test
# Run linter
npm run lint
# Format code
npm run format특허
MIT
Available Tools
1 toolqueryC
Execute a SQL query on a MSSQL database
| Name | Required | Description | Default |
|---|---|---|---|
| connectionString | No | Full connection string (alternative to individual parameters) | |
| host | No | Database server hostname | |
| port | No | Database server port (default: 1433) | |
| database | No | Database name (default: master) | |
| username | No | Database username | |
| password | No | Database password | |
| query | Yes | SQL query to execute | |
| encrypt | No | Enable encryption (default: false) | |
| trustServerCertificate | No | Trust server certificate (default: true) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. While 'Execute a SQL query' implies both read and write operations, it doesn't specify permissions needed, potential side effects, rate limits, or what happens with complex queries. For a database tool with zero annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without any unnecessary words. It's appropriately sized and front-loaded with the essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a database query tool with 9 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain what types of queries are supported, what the return format looks like, error handling, or security considerations. The tool has significant complexity that isn't addressed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, meaning all parameters are documented in the schema itself. The description doesn't add any parameter-specific information beyond what's already in the schema, so it meets the baseline for high schema coverage but doesn't provide additional value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Execute a SQL query') and target resource ('on a MSSQL database'), providing specific verb+resource information. However, with no sibling tools mentioned, there's no opportunity to distinguish from alternatives, preventing a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, prerequisites, or context for usage. It simply states what the tool does without any usage instructions or constraints.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
1 tool update
- First observed
query
TDQS
Scored across 1 tool
With only one tool, there is no possibility of ambiguity or overlap between tools, as there are no other tools to compare it to. The tool's purpose is clearly defined and distinct by default.
Since there is only one tool, it inherently has perfect naming consistency with itself. The tool name 'query' follows a simple verb pattern, and there are no other tools to create inconsistency.
A single tool for an MSSQL server is too few for the apparent scope, as it lacks basic operations like listing tables, describing schemas, or executing parameterized queries. This minimal set will likely cause agent failures due to incomplete functionality.
The tool surface is severely incomplete for an MSSQL database server. While the 'query' tool allows executing SQL, there are significant gaps such as no tools for metadata exploration, transaction management, or data manipulation beyond raw queries, which are essential for typical database workflows.
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