MSSQL MCP Server
MSSQL MCP 服务器
用于连接 Microsoft SQL Server 数据库的模型上下文协议 (MCP) 服务器。此服务器提供用于执行 SQL 查询和管理数据库连接的工具。
安装
通过 Smithery 安装
要通过Smithery自动为 Claude Desktop 安装 MSSQL 数据库连接器:
npx -y @smithery/cli install @knight0zh/mssql-mcp-server --client claude手动安装
npm install mssql-mcp-serverRelated MCP server: SQL MCP Server
用法
将服务器添加到您的 MCP 设置配置文件:
{
"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"
}
}
}
}工具
询问
在 MSSQL 数据库上执行 SQL 查询。
参数
connectionString(字符串,可选):完整的连接字符串(可替代单独的参数)host(字符串,可选):数据库服务器主机名port(数字,可选):数据库服务器端口(默认值:1433)database(字符串,可选):数据库名称(默认值:master)username(字符串,可选):数据库用户名password(字符串,可选):数据库密码query(字符串,必需):要执行的 SQL 查询encrypt(布尔值,可选):启用加密(默认值:false)trustServerCertificate(布尔值,可选):信任服务器证书(默认值:true)
必须提供connectionString或( host + username + password )。
例子
const result = await use_mcp_tool({
server_name: 'mssql',
tool_name: 'query',
arguments: {
host: 'localhost',
username: 'sa',
password: 'yourpassword',
query: 'SELECT * FROM Users',
},
});发展
# 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 format执照
麻省理工学院
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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