LangChain bls labor mcp server bls_dataframe_query
How to: LangChain bls labor mcp server bls_dataframe_query
Add bls labor mcp server 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({
"bls-labor-mcp-server": {
"transport": "streamable_http",
"url": "https://bls-labor.caseyjhand.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 bls_dataframe_query does. LangChain lists the server's tools on connect and calls bls_dataframe_query itself — you do not invoke it by name.
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04
If nothing happens, check the server is running and that bls labor mcp server'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
bls labor mcp server will not start until these are set, so bls_dataframe_query never becomes available.
-
BLS_API_KEY -
MCP_LOG_LEVEL
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.