vanguard memory node for LangChain
io.github.ezumba/vanguard-memory-node
Local deterministic BM25 memory for AI agents. Offline-first, no API key, SHA-256 shards, stdio.
client:LangChain
transport:stdio
runtime:npm
Install vanguard memory node in LangChain
pip install langchain-mcp-adapters
from langchain_mcp_adapters.client import MultiServerMCPClient
client = MultiServerMCPClient({
"vanguard-memory-node": {
"transport": "stdio",
"command": "npx",
"args": ["-y", "@lnes/vanguard-memory-node"],
}
})
tools = await client.get_tools()
get_tools() returns the server's tools as LangChain tools, ready for an agent. LangChain docs