Skip to content

LangChain Scholar Feed fetch_fulltext

How to: LangChain Scholar Feed fetch_fulltext

client:LangChain transport:streamable-http tool:fetch_fulltext

Add Scholar Feed to LangChain

  1. 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({
        "scholar-feed-mcp": {
            "transport": "streamable_http",
            "url": "https://mcp.scholarfeed.org/mcp?src=mcp-registry",
        }
})

tools = await client.get_tools()
  1. 02

    Save the file and restart LangChain.

  2. 03

    Ask for something fetch_fulltext does. LangChain lists the server's tools on connect and calls fetch_fulltext itself — you do not invoke it by name.

  3. 04

    If nothing happens, check the server is running and that Scholar Feed'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

Scholar Feed will not start until these are set, so fetch_fulltext never becomes available.

  • SF_API_KEY

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.