Ein Model Context Protocol (MCP)-Server, der eine sichere Interaktion mit Microsoft SQL Server-Datenbanken ermöglicht. Dieser Server ermöglicht KI-Assistenten das Auflisten von Tabellen, das Lesen von Daten und die Ausführung von SQL-Abfragen über eine kontrollierte Schnittstelle. Dadurch wird die Datenbankerkundung und -analyse sicherer und strukturierter.
Auflisten der verfügbaren SQL Server-Tabellen als Ressourcen
Tabelleninhalt lesen
Ausführen von SQL-Abfragen mit ordnungsgemäßer Fehlerbehandlung
Sicherer Datenbankzugriff durch Umgebungsvariablen
Umfassende Protokollierung
Automatische Installation von Systemabhängigkeiten
Related MCP server: SQL Server MCP
Das Paket installiert automatisch erforderliche Systemabhängigkeiten (wie FreeTDS), wenn es über MCP installiert wird:
pip install mssql-mcp-serverLegen Sie die folgenden Umgebungsvariablen fest:
MSSQL_SERVER=localhost
MSSQL_USER=your_username
MSSQL_PASSWORD=your_password
MSSQL_DATABASE=your_databaseFügen Sie dies zu Ihrer claude_desktop_config.json hinzu:
{
"mcpServers": {
"mssql": {
"command": "uv",
"args": [
"--directory",
"path/to/mssql_mcp_server",
"run",
"mssql_mcp_server"
],
"env": {
"MSSQL_SERVER": "localhost",
"MSSQL_USER": "your_username",
"MSSQL_PASSWORD": "your_password",
"MSSQL_DATABASE": "your_database"
}
}
}
}# Install dependencies
pip install -r requirements.txt
# Run the server
python -m mssql_mcp_server# Clone the repository
git clone https://github.com/RichardHan/mssql_mcp_server.git
cd mssql_mcp_server
# Create virtual environment
python -m venv venv
source venv/bin/activate # or `venv\Scripts\activate` on Windows
# Install development dependencies
pip install -r requirements-dev.txt
# Run tests
pytestÜbernehmen Sie niemals Umgebungsvariablen oder Anmeldeinformationen.
Verwenden Sie einen Datenbankbenutzer mit den minimal erforderlichen Berechtigungen
Erwägen Sie die Implementierung einer Abfrage-Whitelist für den Produktionseinsatz
Überwachen und protokollieren Sie alle Datenbankvorgänge
Dieser MCP-Server benötigt Datenbankzugriff. Aus Sicherheitsgründen:
Erstellen Sie eine dedizierte SQL Server-Anmeldung mit minimalen Berechtigungen
Verwenden Sie niemals SA-Anmeldeinformationen oder Administratorkonten
Beschränken Sie den Datenbankzugriff auf die unbedingt erforderlichen Vorgänge
Aktivieren Sie die Protokollierung für Prüfzwecke
Regelmäßige Sicherheitsüberprüfungen des Datenbankzugriffs
Ausführliche Anweisungen zu folgenden Themen finden Sie im SQL Server-Sicherheitskonfigurationshandbuch :
Erstellen einer eingeschränkten SQL Server-Anmeldung
Festlegen geeigneter Berechtigungen
Überwachen des Datenbankzugriffs
Bewährte Sicherheitsmethoden
⚠️ WICHTIG: Befolgen Sie beim Konfigurieren des Datenbankzugriffs immer das Prinzip der geringsten Privilegien.
MIT-Lizenz – Einzelheiten finden Sie in der Datei LICENSE.
Forken Sie das Repository
Erstellen Sie Ihren Feature-Zweig ( git checkout -b feature/amazing-feature )
Übernehmen Sie Ihre Änderungen ( git commit -m 'Add some amazing feature' )
Pushen zum Zweig ( git push origin feature/amazing-feature )
Öffnen einer Pull-Anfrage
Execute an SQL query on the SQL Server
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | The SQL query to execute |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description fails to disclose whether queries are read-only or can modify data, potential risks like SQL injection, or result formats. This is a significant gap for a tool that can execute arbitrary SQL.
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 very concise at one sentence, but it lacks structure and does not front-load key information beyond the basic action. It could include more detail without becoming verbose.
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?
Given the lack of output schema and annotations, the description is incomplete. It does not explain what the tool returns (e.g., result sets, affected rows), error behavior, or any constraints. Critical context for safe usage is missing.
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?
The input schema has high coverage (100%) and describes the 'query' parameter sufficiently. The description adds no extra meaning beyond what the schema already provides, so a baseline score of 3 is appropriate.
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 verb 'execute' and the resource 'SQL query on the SQL Server', making the purpose straightforward. However, it restates the tool name without adding depth beyond stating it runs queries.
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?
No guidance on when to use this tool or when to avoid it. No mention of prerequisites, security considerations, or alternatives. The description provides no contextual usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
v1.0.0execute_sqlScored across 1 tool
Only one tool exists, so there is no risk of confusion or overlap.
With a single tool, naming is trivially consistent to itself.
A single SQL execution tool is insufficient for the typical scope of SQL Server operations, which usually requires multiple tools for schema exploration, query execution, and data manipulation.
The tool set is severely incomplete; it lacks fundamental operations such as listing tables, describing schemas, or managing databases, limiting useful agent workflows.
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