LangChain TenderCrest AI read_evidence_source
How to: LangChain TenderCrest AI read_evidence_source
Add TenderCrest AI 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({
"tendercrest-ai": {
"transport": "streamable_http",
"url": "https://www.tendercrestai.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 read_evidence_source does. LangChain lists the server's tools on connect and calls read_evidence_source itself — you do not invoke it by name.
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04
If nothing happens, check the server is running and that TenderCrest AI'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 14 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.