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mcp/harbor
LangChain

mem context for LangChain

io.github.turbyho/mem-context

Temporal memory MCP server with LanceDB vector search, weight-decay scoring, and LLM consolidation

client:LangChain transport:stdio runtime:pypi

Install mem context in LangChain

pip install langchain-mcp-adapters 

from langchain_mcp_adapters.client import MultiServerMCPClient

client = MultiServerMCPClient({
        "mem-context": {
            "transport": "stdio",
            "command": "uvx",
            "args": ["mem-context"],
        }
})

tools = await client.get_tools()

get_tools() returns the server's tools as LangChain tools, ready for an agent. LangChain docs

mem context in other clients

mem context MCP server