Empowering LLMs with VikingDB: An MCP Server for Seamless Integration

This document details the VikingDB MCP server, a crucial component for connecting Large Language Models (LLMs) with the high-performance vector database, VikingDB, developed by ByteDance. By leveraging the Model Context Protocol (MCP), this server enables LLMs to access, store, and retrieve information from VikingDB, significantly enhancing their capabilities in various applications.

Understanding VikingDB

VikingDB is a powerful vector database designed for speed and efficiency. For comprehensive information on VikingDB's features and functionalities, refer to the official documentation: VikingDB Documentation

Core Functionality: Tools Implemented

The VikingDB MCP server provides the following tools, enabling LLMs to interact effectively with the database:

vikingdb-collection-intro: Provides detailed information about the specified VikingDB collection, including its schema and metadata. This allows the LLM to understand the structure of the data it's interacting with.
vikingdb-index-intro: Describes the index configuration of the VikingDB index. This helps the LLM understand how data is indexed and optimized for search.
vikingdb-upsert-information: Enables the LLM to insert or update information within VikingDB. This is crucial for building dynamic and evolving knowledge bases.
vikingdb-search-information: Allows the LLM to perform similarity searches within VikingDB, retrieving relevant information based on vector embeddings. This is the core function for contextual retrieval.

Configuration Parameters

To properly connect to your VikingDB instance, the server requires the following configuration parameters:

vikingdb_host: The hostname or IP address of your VikingDB server.
vikingdb_region: The region where your VikingDB instance is located.
vikingdb_ak: Your Access Key for authenticating with VikingDB.
vikingdb_sk: Your Secret Key for authenticating with VikingDB.
collection_name: The name of the VikingDB collection you want to use.
index_name: The name of the index within the specified collection.

Quick Start Guide

Installation via Smithery

The recommended method for installing the VikingDB MCP server is through Smithery, which simplifies the process, especially for Claude Desktop users.

npx -y @smithery/cli install mcp-server-vikingdb --client claude

Configuration for Claude Desktop

After installation, you need to configure Claude Desktop to recognize and utilize the VikingDB MCP server. The configuration file is located at:

MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json
Windows: %APPDATA%/Claude/claude_desktop_config.json

Development/Unpublished Servers Configuration:

{
  "mcpServers": {
    "mcp-server-vikingdb": {
      "command": "uv",
      "args": [
        "--directory",
        "dir to mcp-server-vikingdb",
        "run",
        "mcp-server-vikingdb",
        "--vikingdb-host", 
        "your host",
        "--vikingdb-region", 
        "your region",
        "--vikingdb-ak", 
        "your access key",
        "--vikingdb-sk", 
        "your secret key",
        "--collection-name",
        "your collection name",
        "--index-name",
        "your index name"
      ]
    }
  }
}

Published Servers Configuration:

{
    "mcpServers": {
      "mcp-server-vikingdb": {
        "command": "uvx",
        "args": [
          "mcp-server-vikingdb",
          "--vikingdb-host", 
          "your host",
          "--vikingdb-region", 
          "your region",
          "--vikingdb-ak", 
          "your access key",
          "--vikingdb-sk", 
          "your secret key",
          "--collection-name",
          "your collection name",
          "--index-name",
          "your index name"
      ]
     }
    }
  }

Important: Replace "your host", "your region", "your access key", "your secret key", "your collection name", and "your index name" with your actual VikingDB credentials and configuration.

Development Workflow

Building and Publishing the Package

For developers looking to contribute or customize the VikingDB MCP server, follow these steps:

Synchronize Dependencies and Update Lockfile:
```
uv sync
```
Build Package Distributions:
```
uv build
```
This command generates source and wheel distributions in the dist/ directory.
Publish to PyPI:
```
uv publish
```
Note: You'll need to configure your PyPI credentials using environment variables or command-line flags:
- Token: --token or UV_PUBLISH_TOKEN
- Username/Password: --username/UV_PUBLISH_USERNAME and --password/UV_PUBLISH_PASSWORD

Debugging Strategies

Debugging MCP servers that communicate over standard input/output (stdio) can be challenging. We highly recommend using the MCP Inspector for a streamlined debugging experience.

Launch the MCP Inspector using the following command:

npx @modelcontextprotocol/inspector uv --directory dir_to_mcp_server_vikingdb run mcp-server-vikingdb --vikingdb-host your_host --vikingdb-region your_region --vikingdb-ak your_access_key --vikingdb-sk your_secret_key --collection-name your_collection_name --index-name your_index_name

The Inspector will provide a URL that you can access in your browser to begin debugging your VikingDB MCP server. This tool allows you to inspect the communication between the LLM and the server, making it easier to identify and resolve issues.