VikingDB

VikingDB

kashiwabyte

Connects to VikingDB (ByteDance's vector database) to store and search high-dimensional data. Allows you to upsert and query vectorized information for similarity search applications.

Store and search data using VikingDB vector database.

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What it does

  • Store vectorized data in VikingDB collections
  • Search for similar vectors using semantic queries
  • Manage database collections and indexes
  • Upsert information for later retrieval

Best for

AI applications needing vector similarity searchSemantic search and recommendation systemsRAG (Retrieval Augmented Generation) implementations
Uses ByteDance's high-performance vector databaseBuilt-in collection and index management

About VikingDB

VikingDB is a community-built MCP server published by kashiwabyte that provides AI assistants with tools and capabilities via the Model Context Protocol. Store and search data efficiently with VikingDB, a powerful vector database and vector db alternative to Pinecone and Ex It is categorized under databases.

How to install

You can install VikingDB in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

License

VikingDB is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

MseeP.ai Security Assessment Badge

VikingDB MCP server

Trust Score

smithery badge an mcp server for vikingdb store and search

What is VikingDB

VikingDB is a high-performance vector database developed by ByteDance.

You can easily use it following the doc bellow: https://www.volcengine.com/docs/84313/1254444

Tools

The server implements the following tools:

  • vikingdb-colleciton-intro: introduce the collection of vikingdb

  • vikingdb-index-intro: introduce the index of vikingdb

  • vikingdb-upsert-information: upsert information to vikingdb for later use

  • vikingdb-search-information: searche for information in the VikingDB

Configuration

  • vikingdb_host: The host to use for the VikingDB server.

  • vikingdb_region: The region to use for the VikingDB server.

  • vikingdb_ak: The Access Key to use for the VikingDB server.

  • vikingdb_sk: The Secret Key to use for the VikingDB server.

  • collection_name: The name of the collection to use.

  • index_name: The name of the index to use.

Quickstart

Install

Installing via Smithery

To install VikingDB MCP server for Claude Desktop automatically via Smithery:

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

Claude Desktop

On MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json

On 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"
    ]
   }
  }
} 

Development

Building and Publishing

To prepare the package for distribution:

  1. Sync dependencies and update lockfile:
uv sync
  1. Build package distributions:
uv build

This will create source and wheel distributions in the dist/ directory.

  1. Publish to PyPI:
uv publish

Note: You'll need to set PyPI credentials via environment variables or command flags:

  • Token: --token or UV_PUBLISH_TOKEN
  • Or username/password: --username/UV_PUBLISH_USERNAME and --password/UV_PUBLISH_PASSWORD

Debugging

Since MCP servers run over stdio, debugging can be challenging. For the best debugging experience, we strongly recommend using the MCP Inspector.

You can launch the MCP Inspector via npm with this 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

Upon launching, the Inspector will display a URL that you can access in your browser to begin debugging.

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