Arg2P for LangChain
io.github.tuprolog/arg2p
Structured argumentation: solve ASPIC+, ABA and abstract theories, explore their results
client:LangChain
transport:stdio
runtime:pypi
Install Arg2P in LangChain
pip install langchain-mcp-adapters
from langchain_mcp_adapters.client import MultiServerMCPClient
client = MultiServerMCPClient({
"arg2p": {
"transport": "stdio",
"command": "uvx",
"args": ["arg2p"],
}
})
tools = await client.get_tools()
get_tools() returns the server's tools as LangChain tools, ready for an agent. LangChain docs