LangChain ai·rete·rag get_usage
How to: LangChain ai·rete·rag get_usage
Add ai·rete·rag to LangChain
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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({
"ai-rete-rag-mcp": {
"transport": "streamable_http",
"url": "https://ai-rete-rag.com/mcp",
}
})
tools = await client.get_tools()
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02
Save the file and restart LangChain.
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03
Ask for something get_usage does. LangChain lists the server's tools on connect and calls get_usage itself — you do not invoke it by name.
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04
If nothing happens, check the server is running and that ai·rete·rag'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
Set these first
ai·rete·rag will not start until these are set, so get_usage never becomes available.
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AI_RETE_RAG_API_KEY -
AI_RETE_RAG_API_URL
Same tool, other clients
This list was read from the server itself, by connecting to it and calling tools/list on 24 September 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.