VikingDB
A server for storing and searching data in a VikingDB instance, configurable via command line or environment variables.
VikingDB MCP server
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Development/Unpublished Servers Configuration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:
- Sync dependencies and update lockfile:
uv sync
- Build package distributions:
uv build
This will create source and wheel distributions in the dist/ directory.
- Publish to PyPI:
uv publish
Note: You'll need to set PyPI credentials via environment variables or command flags:
- Token:
--tokenorUV_PUBLISH_TOKEN - Or username/password:
--username/UV_PUBLISH_USERNAMEand--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.
Verwandte Server
Redshift MCP Server
An MCP server for Amazon Redshift, allowing AI assistants to interact with Redshift databases.
MCP Trino Server
Integrates with Trino and Iceberg for advanced data exploration, querying, and table maintenance.
World Bank MCP Server
Interact with the open World Bank data API to list and analyze economic and development indicators for various countries.
FRED Economic Data
Access economic data from the Federal Reserve Bank of St. Louis (FRED).
MCP Persistence
MCP Persistence: your AI Agent now creates and manages databases on its own
Zurich Open Data MCP Server
Enables Claude, ChatGPT, and other MCP-compatible AI assistants to directly query 900+ datasets, geodata, parliamentary proceedings, tourism data, linked data, and real-time environmental and mobility information from the City of Zurich. 20 Tools, 6 Resources, 6 APIs.
Seatable
A comprehensive Model Context Protocol (MCP) server for SeaTable that exposes end‑to‑end database capabilities (schema introspection, CRUD, querying, linking, select option management, and file attachment stubs) through 18+ rigorously defined tools.
BigQuery Analysis
Execute and validate SQL queries against Google BigQuery. It safely runs SELECT queries under 1TB and returns results in JSON format.
MCP Simple PubMed
Access PubMed articles through the Entrez API.
mnemon-mcp
Persistent layered memory for AI agents — 4-layer model, FTS5 search, fact versioning, EN+RU stemming. Local-first, zero-cloud, single SQLite file.
