What does mcp-lance-db do?
It is a basic MCP server that stores text as vector embeddings in LanceDB and retrieves memories that are semantically similar to a query.
@kyryl-opens-ml
基本信息
暂无概览
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"mcp-server-lancedb": {
"command": "uv",
"args": [
"sync"
]
}
}
}Adds a new memory to the vector database
Retrieves semantically similar memories
mcp-lance-db is a Model Context Protocol server that stores and retrieves memories in the LanceDB vector database. It acts as a semantic memory layer for LLM applications, allowing text to be stored with vector embeddings for later retrieval.
Configure it in your MCP client (e.g., Claude Desktop) by adding the command uvx mcp-lance-db to the client’s config file. For Claude Desktop, the config file is claude_desktop_config.json. The server then exposes two tools: add-memory and search-memories.
It is a basic MCP server that stores text as vector embeddings in LanceDB and retrieves memories that are semantically similar to a query.
It provides two tools: `add-memory` (takes a required `content` string) and `search-memories` (takes a required `query` string and optional `limit` parameter).
Database path is `./lancedb`, collection name is `memories`, embedding model is `BAAI/bge-small-en-v1.5` on CPU, and the similarity threshold is 0.7.
Use the MCP Inspector: run `npx @modelcontextprotocol/inspector uv --directory $(PWD) run mcp-lance-db` and open the provided URL in a browser.
It is distributed as a Python package and can be run via `uvx mcp-lance-db`. No manual installation is needed if using `uv`.
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