MCP Toolbox LangChain SDK

This SDK allows you to seamlessly integrate the functionalities of MCP Toolbox into your LangChain GenAI applications, enabling advanced orchestration and interaction with LLMs.

For detailed guides, authentication examples, and advanced configuration, visit the Python SDK Langchain Guide.

Table of Contents

• Installation
• Quickstart
• Usage
• Contributing
• License
• Support

Installation

pip install toolbox-langchain

Quickstart

Here's a minimal example to get you started using LangGraph:

from toolbox_langchain import ToolboxClient
from langchain_google_vertexai import ChatVertexAI
from langgraph.prebuilt import create_react_agent

async with ToolboxClient("http://127.0.0.1:5000") as toolbox:
    tools = toolbox.load_toolset()

    model = ChatVertexAI(model="gemini-3-flash-preview")
    agent = create_react_agent(model, tools)

    prompt = "How's the weather today?"

    for s in agent.stream({"messages": [("user", prompt)]}, stream_mode="values"):
        message = s["messages"][-1]
        if isinstance(message, tuple):
            print(message)
        else:
            message.pretty_print()

Usage

The toolbox-langchain package provids a dedicated integration to seamlessly load and use MCP Toolbox tools within the LangChain orchestration framework. For detailed guides and advanced configuration, please visit the following sections on our Documentation Site:

• Transport Protocols
• Loading Tools
• Use with Langchain
• Use with Langraph
• Manual Usage
• Client to Server Authentication
• Authenticating Tools
• Binding Parameter Values
• Asynchronous Usage
• OpenTelemetry

Contributing

Contributions are welcome! Please refer to the DEVELOPER.md file for guidelines on how to set up a development environment and run tests.

License

This project is licensed under the Apache License 2.0. See the LICENSE file for details.

Support

If you encounter issues or have questions, check the existing GitHub Issues for the main Toolbox project.