MCP Database Server

What does “MCP Database Server” MCP Server do?

The MCP Database Server is a Model Context Protocol (MCP) server designed to provide seamless database access capabilities for AI assistants and development tools such as Claude. It enables secure and programmatic connectivity with a variety of popular database systems, including SQLite, SQL Server, PostgreSQL, and MySQL. By functioning as a bridge between AI-powered agents and external databases, MCP Database Server empowers developers to perform database queries, manage content, and interact with structured data directly from their workflows or automation pipelines. This integration enhances productivity by allowing routine tasks, such as querying records or updating tables, to be executed efficiently and consistently, thereby improving the ability to build context-aware AI applications.

List of Prompts

No prompt templates are explicitly mentioned in the repository or documentation.

List of Resources

No explicit MCP “resources” are detailed in the available documentation or codebase.

List of Tools

No direct list of MCP “tools” is provided in the documentation or server file index.

Use Cases of this MCP Server

• Database Management
  Enables AI assistants or scripts to securely connect to and manage multiple types of databases (SQLite, SQL Server, PostgreSQL, MySQL), supporting operations such as querying, updating, and schema exploration.

• Data Analytics and Reporting
  Facilitates automated data retrieval and aggregation for reporting purposes, allowing users to ask questions about data stored in various databases and receive structured responses.

• Automation Integration
  Serves as a backend for workflow automation systems that require real-time database access, such as updating records when certain triggers occur or generating alerts based on database changes.

• Application Development Support
  Provides backend connectivity for developing AI-driven applications that require dynamic read/write access to enterprise or local databases.

How to set it up

Windsurf

1. Ensure Node.js is installed on your system.
2. Install the MCP Database Server globally:

   npm install -g @executeautomation/database-server@latest
   

3. Open the Windsurf configuration file (usually windsurf.config.json).
4. Add the MCP Database Server entry:

   {
     "mcpServers": {
       "database-server": {
         "command": "database-server",
         "args": []
       }
     }
   }
   

5. Save and restart Windsurf. Verify connectivity in the MCP dashboard.

Securing API Keys
Store sensitive credentials using environment variables:

{
  "env": {
    "DB_PASSWORD": "your_password"
  },
  "inputs": {
    "password": "${DB_PASSWORD}"
  }
}

Claude

1. Install Node.js if not already present.
2. Globally install the MCP Database Server:

   npm install -g @executeautomation/database-server@latest
   

3. Update Claude’s MCP configuration file with:

   {
     "mcpServers": {
       "database-server": {
         "command": "database-server",
         "args": []
       }
     }
   }
   

4. Save, restart Claude, and confirm the MCP server is accessible.

Securing API Keys
Set credentials as environment variables and reference them in configuration.

Cursor

1. Make sure Node.js is installed.
2. Run:

   npm install -g @executeautomation/database-server@latest
   

3. Edit Cursor’s cursor.config.json to include:

   {
     "mcpServers": {
       "database-server": {
         "command": "database-server",
         "args": []
       }
     }
   }
   

4. Save and restart Cursor. Check for successful server registration.

Securing API Keys
Utilize environment variables as shown in other examples.

Cline

1. Ensure Node.js is installed.
2. Install the server globally:

   npm install -g @executeautomation/database-server@latest
   

3. Update cline.config.json:

   {
     "mcpServers": {
       "database-server": {
         "command": "database-server",
         "args": []
       }
     }
   }
   

4. Save, restart Cline, and confirm the MCP Database Server is running.

Securing API Keys
Reference credentials via environment variables as shown above.

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "database-server": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “database-server” to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.

Overview

Based on the available information, MCP Database Server focuses on robust database connectivity and offers standard setup practices, but lacks detailed MCP prompt, resource, and tool documentation in the public repository.

Our opinion

This MCP provides solid database integration for AI workflows and is well documented for installation and usage. However, it is missing explicit MCP prompt, resource, and tool definitions, which are important for maximizing usability and interoperability in MCP-based environments.

MCP Score

Rating:
Based on the two tables above, this MCP scores a 5/10. It is reliable and open source, with clear setup instructions and meaningful use cases, but lacks explicit MCP prompt, resource, and tool definitions that would significantly enhance its utility and interoperability.