LangChain TuneViva get_practice_score
How to: LangChain TuneViva get_practice_score
Add TuneViva to LangChain
-
01
Open pip install langchain-mcp-adapters and merge this in. Keep any servers already there.
from langchain_mcp_adapters.client import MultiServerMCPClient
client = MultiServerMCPClient({
"tuneviva": {
"transport": "streamable_http",
"url": "https://tuneviva.com/mcp",
}
})
tools = await client.get_tools()
-
02
Save the file and restart LangChain.
-
03
Ask for something get_practice_score does. LangChain lists the server's tools on connect and calls get_practice_score itself — you do not invoke it by name.
-
04
If nothing happens, check the server is running and that TuneViva's identifier in your config matches the one above exactly.
get_tools() returns the server's tools as LangChain tools, ready for an agent. LangChain docs
Same tool, other clients
This list was read from the server itself, by connecting to it and calling tools/list on 8 November 2026. It is what
the server actually exposes, not what its listing claims.
Mutating and Read-only are read off each tool's name, not its schema — a hint, not a guarantee. The registry stores tool names only; connect the server for its live schemas.