KWDB MCP Server Integration

What does “KWDB” MCP Server do?

The KWDB MCP Server is an implementation of the Model Context Protocol (MCP) that connects AI assistants with the KWDB database, providing business intelligence and data manipulation capabilities. Acting as a bridge, the KWDB MCP Server enables AI models to perform database queries, retrieve metadata, modify data, and access syntax guides through standardized tools and resources. It supports both reading and writing operations (e.g., SELECT, INSERT, UPDATE, DDL), automatically manages query limits for efficiency, and formats all API responses in a consistent JSON structure. This server enhances development workflows by simplifying database access, ensuring security with distinct tools for read/write, and exposing useful metadata and table schemas to clients for rich, context-aware LLM interactions.

List of Prompts

• Syntax Guide: Access a comprehensive syntax guide for KWDB through predefined prompt templates, enabling users and LLMs to follow correct SQL syntax when interacting with the database.

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List of Resources

• Product information (kwdb://product_info): Contains information about the KWDB product version and supported features.
• Database metadata (kwdb://db_info/{database_name}): Provides details about a specific database, including engine type, comments, and contained tables.
• Table schema (kwdb://table/{table_name}): Exposes the schema of a specific table, including columns and example queries.

List of Tools

• read-query: Executes read-only SQL operations like SELECT, SHOW, and EXPLAIN on the KWDB database.
• write-query: Executes modifying SQL operations such as INSERT, UPDATE, DELETE, and DDL commands (CREATE, DROP, ALTER).

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Use Cases of this MCP Server

• Database Management: Enables developers to execute both read and write commands on the KWDB database, streamlining data manipulation and schema changes directly from AI-assisted interfaces.
• Business Intelligence: Facilitates querying of business data and analysis by exposing structured data access through LLMs, supporting reporting and dashboard use cases.
• Codebase Exploration for Data: Allows developers or AI agents to retrieve table schemas and metadata, making it easier to understand and interact with large or unfamiliar KWDB databases.
• API Integration for Data-Driven Apps: Connects applications or AI workflows to KWDB as a backend, exposing standardized endpoints for data retrieval and manipulation.
• Automated Syntax Guidance: Provides LLMs and users with syntax prompts and guides, reducing SQL errors and improving development efficiency.

How to set it up

Windsurf

1. Ensure prerequisites are met (e.g., Node.js and MCP-compatible environment).
2. Locate the Windsurf configuration file (e.g., windsurf.config.json).
3. Add the KWDB MCP Server to the mcpServers object with the appropriate command and arguments.
4. Save the configuration and restart Windsurf.
5. Verify the KWDB MCP Server appears in the available MCP servers list.

Example JSON configuration:

{
  "mcpServers": {
    "kwdb": {
      "command": "npx",
      "args": ["@KWDB/mcp-server@latest"]
    }
  }
}

Securing API keys:

{
  "mcpServers": {
    "kwdb": {
      "command": "npx",
      "args": ["@KWDB/mcp-server@latest"],
      "env": {
        "KWDB_API_KEY": "${KWDB_API_KEY}"
      },
      "inputs": {
        "database_url": "your_kwdb_connection_string"
      }
    }
  }
}

Claude

1. Confirm required dependencies are present.
2. Open Claude’s MCP server configuration file.
3. Add the KWDB MCP Server configuration under mcpServers.
4. Save changes and restart Claude or reload configurations.
5. Check for KWDB MCP Server registration.

Example JSON configuration:

{
  "mcpServers": {
    "kwdb": {
      "command": "npx",
      "args": ["@KWDB/mcp-server@latest"]
    }
  }
}

Securing API keys:

{
  "mcpServers": {
    "kwdb": {
      "command": "npx",
      "args": ["@KWDB/mcp-server@latest"],
      "env": {
        "KWDB_API_KEY": "${KWDB_API_KEY}"
      },
      "inputs": {
        "database_url": "your_kwdb_connection_string"
      }
    }
  }
}

Cursor

1. Install Node.js and ensure MCP support is present.
2. Edit the Cursor configuration file (e.g., .cursorrc).
3. Add the KWDB MCP Server entry with command and arguments.
4. Save the file and restart Cursor.
5. Confirm KWDB MCP Server appears in the MCP server list.

Example JSON configuration:

{
  "mcpServers": {
    "kwdb": {
      "command": "npx",
      "args": ["@KWDB/mcp-server@latest"]
    }
  }
}

Securing API keys:

{
  "mcpServers": {
    "kwdb": {
      "command": "npx",
      "args": ["@KWDB/mcp-server@latest"],
      "env": {
        "KWDB_API_KEY": "${KWDB_API_KEY}"
      },
      "inputs": {
        "database_url": "your_kwdb_connection_string"
      }
    }
  }
}

Cline

1. Meet all prerequisites for MCP server integration.
2. Update Cline’s configuration to include the KWDB MCP Server.
3. Insert the server command and args under mcpServers.
4. Save and restart Cline.
5. Validate the server is running as expected.

Example JSON configuration:

{
  "mcpServers": {
    "kwdb": {
      "command": "npx",
      "args": ["@KWDB/mcp-server@latest"]
    }
  }
}

Securing API keys:

{
  "mcpServers": {
    "kwdb": {
      "command": "npx",
      "args": ["@KWDB/mcp-server@latest"],
      "env": {
        "KWDB_API_KEY": "${KWDB_API_KEY}"
      },
      "inputs": {
        "database_url": "your_kwdb_connection_string"
      }
    }
  }
}

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:

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

Overview

Our opinion

The KWDB MCP Server offers clear documentation for its main features, tools, and resources, with solid support for basic MCP integrations. However, prompt templates are limited (only syntax guide is documented), and there’s no explicit information on Roots or Sampling support. Its utility for standard database operations is strong, but coverage of advanced MCP/LLM features is average.

MCP Score: 6/10

MCP Score