Bind MCP tools to a ChatSnowflake instance.
This function filters MCP tools for compatibility, converts them to LangChain Tools, and binds them to the provided LLM using bind_tools().
bind_mcp_tools(
llm,
mcp_tools: List[Any],
mcp_session,
include_patterns: Optional[List[str]] = None,
exclude_patterns: Optional[List[str]] = None,
**bind_kwargs = {}
)Example:
from langchain_snowflake import ChatSnowflake, bind_mcp_tools from langchain_mcp_adapters import load_mcp_tools
Load MCP tools
mcp_tools = await load_mcp_tools(mcp_session)
Create ChatSnowflake instance
llm = ChatSnowflake(...)
Bind MCP tools
agent = bind_mcp_tools( ... llm, ... mcp_tools, ... mcp_session, ... include_patterns=["database", "query"], ... exclude_patterns=["admin"] ... )
Use the agent
response = await agent.ainvoke("List all databases")
| Name | Type | Description |
|---|---|---|
llm* | unknown | ChatSnowflake instance or compatible LLM |
mcp_tools* | List[Any] | List of MCP tools to bind |
mcp_session* | unknown | MCP session for tool execution |
include_patterns | Optional[List[str]] | Default: NoneOptional patterns to include specific tools |
exclude_patterns | Optional[List[str]] | Default: NoneOptional patterns to exclude specific tools |
**bind_kwargs | unknown | Default: {}Additional arguments passed to bind_tools() |