SingleStore MCP Server Integration

What does “SingleStore” MCP Server do?

The SingleStore MCP Server is a Model Context Protocol (MCP) server designed to bridge AI assistants with the SingleStore Management API and related services. By adhering to the MCP standard, this server enables seamless integration, allowing AI clients like Claude Desktop, Cursor, and others to interact with SingleStore databases using natural language. Its primary function is to facilitate complex operations—such as database queries, management tasks, and service interactions—via a unified, standardized protocol. This enhances developer workflows by making it easier to access, manipulate, and manage data within SingleStore environments directly from AI-driven tools, thereby streamlining development, data analysis, and operational tasks.

List of Prompts

No prompt templates are explicitly mentioned in the repository.

List of Resources

No explicit resources are listed in the repository documentation or files.

List of Tools

No explicit tools are listed in the documentation or within files referenced (such as server.py or similar).

Use Cases of this MCP Server

• Database Management: Enables developers to manage SingleStore databases (e.g., create, modify, or delete databases) through natural language using compatible AI clients.
• Service Orchestration: Facilitates the orchestration of SingleStore services and clusters, making operational workflows more accessible through conversational interfaces.
• Query Execution: Allows users to perform complex SQL queries on SingleStore databases via supported AI assistants, streamlining data analysis and reporting.
• Automated Configuration: Simplifies the initialization and configuration of SingleStore environments using guided AI interactions.
• Operational Monitoring: Supports monitoring and health checks of SingleStore instances through AI-enabled commands.

How to set it up

Windsurf

1. Ensure Python >= v3.11.0 and uvx are installed.
2. Install the MCP server with:

   uvx singlestore-mcp-server init --api-key <SINGLESTORE_API_KEY>
   

3. Locate the Windsurf configuration file (the init command may auto-locate it).
4. Add the server to your MCP configuration:

   {
     "mcpServers": {
       "singlestore": {
         "command": "uvx",
         "args": ["singlestore-mcp-server", "serve"]
       }
     }
   }
   

5. Save the file, restart the client, and verify connectivity.

Securing API Keys

Set API keys using environment variables:

{
  "mcpServers": {
    "singlestore": {
      "command": "uvx",
      "args": ["singlestore-mcp-server", "serve"],
      "env": {
        "SINGLESTORE_API_KEY": "your_api_key_here"
      },
      "inputs": {}
    }
  }
}

Claude

1. Ensure Python >= v3.11.0, uvx, and Claude Desktop are installed.
2. Run:

   uvx singlestore-mcp-server init --api-key <SINGLESTORE_API_KEY> --client=claude
   

3. Find the Claude configuration file (the init command usually locates it).
4. Insert the following snippet:

   {
     "mcpServers": {
       "singlestore": {
         "command": "uvx",
         "args": ["singlestore-mcp-server", "serve"]
       }
     }
   }
   

5. Save, restart Claude Desktop, and verify the setup.

Securing API Keys

{
  "mcpServers": {
    "singlestore": {
      "command": "uvx",
      "args": ["singlestore-mcp-server", "serve"],
      "env": {
        "SINGLESTORE_API_KEY": "your_api_key_here"
      },
      "inputs": {}
    }
  }
}

Cursor

1. Confirm Python >= v3.11.0, uvx, and Cursor are installed.
2. Install with:

   uvx singlestore-mcp-server init --api-key <SINGLESTORE_API_KEY> --client=cursor
   

3. Locate the Cursor MCP configuration file.
4. Add the server:

   {
     "mcpServers": {
       "singlestore": {
         "command": "uvx",
         "args": ["singlestore-mcp-server", "serve"]
       }
     }
   }
   

5. Save and restart Cursor to activate.

Securing API Keys

{
  "mcpServers": {
    "singlestore": {
      "command": "uvx",
      "args": ["singlestore-mcp-server", "serve"],
      "env": {
        "SINGLESTORE_API_KEY": "your_api_key_here"
      },
      "inputs": {}
    }
  }
}

Cline

1. Ensure Python >= v3.11.0, uvx, and Cline are installed.
2. Run:

   uvx singlestore-mcp-server init --api-key <SINGLESTORE_API_KEY> --client=cline
   

3. Locate your Cline MCP configuration file.
4. Add this config:

   {
     "mcpServers": {
       "singlestore": {
         "command": "uvx",
         "args": ["singlestore-mcp-server", "serve"]
       }
     }
   }
   

5. Save and restart Cline to complete setup.

Securing API Keys

{
  "mcpServers": {
    "singlestore": {
      "command": "uvx",
      "args": ["singlestore-mcp-server", "serve"],
      "env": {
        "SINGLESTORE_API_KEY": "your_api_key_here"
      },
      "inputs": {}
    }
  }
}

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:

{
  "singlestore": {
    "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 “singlestore” to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.

Overview

I would rate this MCP server a 5/10. The project is well-licensed, has some community traction, and setup is well-documented for multiple platforms. However, the lack of detailed documentation on prompts, resources, and available tools limits its usefulness and discoverability for new users.

MCP Score