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LangChain Sahadeva reconstruct_worked_example

How to: LangChain Sahadeva reconstruct_worked_example

client:LangChain transport:streamable-http tool:reconstruct_worked_example

Add Sahadeva 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({
        "sahadeva": {
            "transport": "streamable_http",
            "url": "https://sahadeva.magicteams.ai/mcp",
        }
})

tools = await client.get_tools()
  1. 02

    Save the file and restart LangChain.

  2. 03

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

  3. 04

    If nothing happens, check the server is running and that Sahadeva'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 5 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.