YDB MCP Server Integration

What does “YDB” MCP Server do?

The YDB MCP (Model Context Protocol) Server is a bridge that connects AI assistants and large language models (LLMs) with YDB databases. By implementing the MCP standard, the YDB MCP Server enables LLMs to perform database operations and interact with YDB instances using natural language. This integration facilitates AI-powered workflows, allowing developers and users to query, manage, and manipulate YDB databases seamlessly through their AI tools. It enhances development productivity by making database access and management more intuitive and accessible, removing the need for manual SQL queries or direct database manipulation. The YDB MCP Server is ideal for scenarios where natural language interfaces to databases can drive automation, data retrieval, and management tasks.

List of Prompts

No prompt templates are mentioned in the available documentation or codebase.

List of Resources

No explicit resources are listed in the available documentation or codebase.

List of Tools

No explicit tool definitions are found in the available documentation, README, or visible files. The precise tools (e.g., query_database, list_tables) exposed by the YDB MCP server are not specified.

Use Cases of this MCP Server

• AI-driven Database Querying: Allow LLMs to access and query YDB databases using natural language, enabling non-technical users to retrieve data without writing SQL.
• Automated Database Management: Enable automated tasks such as database schema inspection and simple data manipulations via AI assistants.
• Secure Data Access: Integrate with existing authentication systems (anonymous or login/password) to provide secure, credentialed access to YDB databases for AI-powered agents.
• LLM-powered Data Analysis: Facilitate the use of LLMs for analyzing data stored in YDB, generating insights or summaries that can be surfaced directly to users.
• Enhanced Development Workflows: Streamline development processes by allowing developers to interact with YDB instances as part of their AI-augmented toolchains.

How to set it up

Windsurf

1. Prerequisites: Ensure you have Node.js and either uv (for uvx) or pipx installed.
2. Locate Configuration: Open your project’s configuration file (e.g., windsurf.json).
3. Add YDB MCP Server: Include the YDB MCP server configuration in the mcpServers section:

   {
     "mcpServers": {
       "ydb": {
         "command": "uvx",
         "args": [
           "ydb-mcp",
           "--ydb-endpoint", "grpc://localhost:2136/local"
         ]
       }
     }
   }
   

4. (Optional) Use Login/Password Authentication:

   {
     "mcpServers": {
       "ydb": {
         "command": "uvx",
         "args": [
           "ydb-mcp",
           "--ydb-endpoint", "grpc://localhost:2136/local",
           "--ydb-auth-mode", "login-password",
           "--ydb-login", "<your-username>",
           "--ydb-password", "<your-password>"
         ]
       }
     }
   }
   

5. Restart and Verify: Restart Windsurf and verify the server is accessible.

Claude

1. Prerequisites: Install Node.js and pipx or uvx as required.
2. Configuration File: Edit the Claude configuration file to add the MCP server.
3. Add YDB MCP Server:

   {
     "mcpServers": {
       "ydb": {
         "command": "pipx",
         "args": [
           "run", "ydb-mcp",
           "--ydb-endpoint", "grpc://localhost:2136/local"
         ]
       }
     }
   }
   

4. (Optional) Login/Password: Use the same authentication snippet as above.
5. Save and Restart: Save your changes and restart Claude.

Cursor

1. Install Prerequisites: Ensure pipx or uvx is installed.
2. Edit Configuration: Open Cursor’s configuration file.
3. Add YDB MCP Server:

   {
     "mcpServers": {
       "ydb": {
         "command": "uvx",
         "args": [
           "ydb-mcp",
           "--ydb-endpoint", "grpc://localhost:2136/local"
         ]
       }
     }
   }
   

4. Save and Restart: Save configuration and restart Cursor.
5. Verify: Confirm connection to the YDB MCP server.

Cline

1. Prepare Environment: Make sure pipx or uvx is available in your environment.
2. Open Configuration: Edit the relevant configuration file for Cline.
3. Configure MCP Server:

   {
     "mcpServers": {
       "ydb": {
         "command": "pipx",
         "args": [
           "run", "ydb-mcp",
           "--ydb-endpoint", "grpc://localhost:2136/local"
         ]
       }
     }
   }
   

4. Add Authentication if Needed:

   {
     "mcpServers": {
       "ydb": {
         "command": "pipx",
         "args": [
           "run", "ydb-mcp",
           "--ydb-endpoint", "grpc://localhost:2136/local",
           "--ydb-auth-mode", "login-password",
           "--ydb-login", "<your-username>",
           "--ydb-password", "<your-password>"
         ]
       }
     }
   }
   

5. Restart and Test: Restart Cline and test the integration.

Securing API Keys

Use environment variables to store sensitive information. Example:

{
  "mcpServers": {
    "ydb": {
      "command": "pipx",
      "args": [
        "run", "ydb-mcp",
        "--ydb-endpoint", "grpc://localhost:2136/local"
      ],
      "env": {
        "YDB_LOGIN": "<your-username>",
        "YDB_PASSWORD": "<your-password>"
      },
      "inputs": {
        "ydb-login": "${YDB_LOGIN}",
        "ydb-password": "${YDB_PASSWORD}"
      }
    }
  }
}

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:

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

Overview

Our overall impression is that YDB MCP is a focused integration for enabling AI-driven YDB database interactions, with clear setup instructions. However, the lack of explicit prompt, tool, and resource documentation reduces its out-of-the-box agentic and composability potential.

MCP Score

Rating:
Based on the completeness of documentation, presence of a license, and integration focus, but absence of explicit tool/resource/prompt support, I would rate this MCP server a 5 out of 10. It has potential, but lacks detailed agentic composability information typical of more mature MCP servers.