How to integrate Stormboard MCP with LangChain

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Introduction

This guide walks you through connecting Stormboard to LangChain using the Composio tool router. By the end, you'll have a working Stormboard agent that can summarize all sticky notes on a board, add action items to a stormboard project, list team members assigned to a board through natural language commands.

This guide will help you understand how to give your LangChain agent real control over a Stormboard account through Composio's Stormboard MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Connect your Stormboard project to Composio
  • Create a Tool Router MCP session for Stormboard
  • Initialize an MCP client and retrieve Stormboard tools
  • Build a LangChain agent that can interact with Stormboard
  • Set up an interactive chat interface for testing

What is LangChain?

LangChain is a framework for developing applications powered by language models. It provides tools and abstractions for building agents that can reason, use tools, and maintain conversation context.

Key features include:

  • Agent Framework: Build agents that can use tools and make decisions
  • MCP Integration: Connect to external services through Model Context Protocol adapters
  • Memory Management: Maintain conversation history across interactions
  • Multi-Provider Support: Works with OpenAI, Anthropic, and other LLM providers

What is the Stormboard MCP server, and what's possible with it?

The Stormboard MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Stormboard account. It provides structured and secure access so your agent can perform Stormboard operations on your behalf.

Supported Tools & Triggers

Tools
Accept a Storm InviteTool to accept a Storm invitation and join the Storm.
Add a Favorite StarTool to add a favorite star to a Storm on the Dashboard.
Check AuthenticationTool to verify API key authentication validity.
Close a StormTool to close an open Storm, making it read-only.
Create a Line ConnectorTool to create a line connector between two ideas.
Create a new chat messageTool to create a new chat message in a Stormboard storm.
Create a New StormTool to create a new Storm in Stormboard for interactive planning and collaboration.
Create a New TagTool to create a new tag in a Storm without any data related to Ideas.
Create a New UserTool to create a new user account in Stormboard.
Create an idea in StormboardTool to create a new idea in an existing Stormboard storm.
Create Tag Data for an IdeaTool to update tag data for an idea.
Decline a Storm InviteTool to decline a Storm invitation and remove it from your list.
Delete a Connector Between IdeasTool to delete a line connector between two ideas.
Delete a Specific ConnectorTool to delete a line connector using the connector ID.
Get Storm DetailsTool to retrieve detailed information about a specific Storm.
Duplicate a StormTool to duplicate an existing Storm.
Get a list of connectors in a StormTool to retrieve a list of connectors within a specific Storm.
Get a List of IdeasTool to retrieve all ideas from a Storm.
Get A List Of ParticipantsTool to retrieve a list of all participants in a Storm.
Get A List Of Storms InvitesTool to retrieve a list of storms that you have been invited to.
Get List of Tags in StormTool to retrieve the list of tags that have been created in a Storm.
Get A List Of Your StormsTool to retrieve a list of storms from Stormboard.
Get Authentication InfoTool to retrieve authentication information and API token for the authenticated user.
Get Chat MessagesTool to retrieve a list of chat messages from a Stormboard storm.
Get Idea DataTool to retrieve detailed data and metadata for a specific idea.
Get Info About Your UserTool to retrieve authenticated user profile information.
Get My Storm AccessTool to check if the authenticated user has access to a Storm and retrieve their permission level.
Get Storm TemplateTool to retrieve template data for a Storm including all sections and subsections.
Get Tag Data For An IdeaTool to retrieve tag data for a specific idea in Stormboard.
Get Unread Chat MessagesTool to retrieve unread chat messages from a specific Storm.
Invite Participants to StormTool to invite people to join a Storm by email.
Join a StormTool to join a Storm using its ID and access key.
Mark Chat Messages as ReadTool to mark all chat messages as read in a Storm.
Remove a Favorite StarTool to remove a favorite star from a Storm on the Dashboard.
Reopen a StormTool to reopen a closed Storm.
Update a Line ConnectorTool to update a specific line connector between two ideas.
Update NotificationsTool to update user notification preferences.
Update Section in StormTool to update a section's title, description, and/or character in a Storm.
Update Storm LegendTool to update the color labels of the legend for a storm.
Update Your ProfileTool to update your user profile information.
Verify Your AccountTool to verify a Stormboard account using a verification code.

What is the Composio tool router, and how does it fit here?

What is Tool Router?

Composio's Tool Router helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Tool Router

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Tool Router works

The Tool Router follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Prerequisites

Before starting this tutorial, make sure you have:
  • Python 3.10 or higher installed on your system
  • A Composio account with an API key
  • An OpenAI API key
  • Basic familiarity with Python and async programming

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key. You'll need credits to use the models, or you can connect to another model provider.
  • Keep the API key safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.

Install dependencies

pip install composio-langchain langchain-mcp-adapters langchain python-dotenv

Install the required packages for LangChain with MCP support.

What's happening:

  • composio-langchain provides Composio integration for LangChain
  • langchain-mcp-adapters enables MCP client connections
  • langchain is the core agent framework
  • python-dotenv loads environment variables

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_composio_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your requests to Composio's API
  • COMPOSIO_USER_ID identifies the user for session management
  • OPENAI_API_KEY enables access to OpenAI's language models

Import dependencies

from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()
What's happening:
  • We're importing LangChain's MCP adapter and Composio SDK
  • The dotenv import loads environment variables from your .env file
  • This setup prepares the foundation for connecting LangChain with Stormboard functionality through MCP

Initialize Composio client

async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))

    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
What's happening:
  • We're loading the COMPOSIO_API_KEY from environment variables and validating it exists
  • Creating a Composio instance that will manage our connection to Stormboard tools
  • Validating that COMPOSIO_USER_ID is also set before proceeding

Create a Tool Router session

# Create Tool Router session for Stormboard
session = composio.create(
    user_id=os.getenv("COMPOSIO_USER_ID"),
    toolkits=['stormboard']
)

url = session.mcp.url
What's happening:
  • We're creating a Tool Router session that gives your agent access to Stormboard tools
  • The create method takes the user ID and specifies which toolkits should be available
  • The returned session.mcp.url is the MCP server URL that your agent will use
  • This approach allows the agent to dynamically load and use Stormboard tools as needed

Configure the agent with the MCP URL

client = MultiServerMCPClient({
    "stormboard-agent": {
        "transport": "streamable_http",
        "url": session.mcp.url,
        "headers": {
            "x-api-key": os.getenv("COMPOSIO_API_KEY")
        }
    }
})

tools = await client.get_tools()

agent = create_agent("gpt-5", tools)
What's happening:
  • We're creating a MultiServerMCPClient that connects to our Stormboard MCP server via HTTP
  • The client is configured with a name and the URL from our Tool Router session
  • get_tools() retrieves all available Stormboard tools that the agent can use
  • We're creating a LangChain agent using the GPT-5 model

Set up interactive chat interface

conversation_history = []

print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Stormboard related question or task to the agent.\n")

while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ['exit', 'quit', 'bye']:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    conversation_history.append({"role": "user", "content": user_input})
    print("\nAgent is thinking...\n")

    response = await agent.ainvoke({"messages": conversation_history})
    conversation_history = response['messages']
    final_response = response['messages'][-1].content
    print(f"Agent: {final_response}\n")
What's happening:
  • We initialize an empty conversation_history list to maintain context across interactions
  • A while loop continuously accepts user input from the command line
  • When a user types a message, it's added to the conversation history and sent to the agent
  • The agent processes the request using the ainvoke() method with the full conversation history
  • Users can type 'exit', 'quit', or 'bye' to end the chat session gracefully

Run the application

if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • We call the main() function using asyncio.run() to start the application

Complete Code

Here's the complete code to get you started with Stormboard and LangChain:

from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()

async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    
    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
    
    session = composio.create(
        user_id=os.getenv("COMPOSIO_USER_ID"),
        toolkits=['stormboard']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "stormboard-agent": {
            "transport": "streamable_http",
            "url": url,
            "headers": {
                "x-api-key": os.getenv("COMPOSIO_API_KEY")
            }
        }
    })
    
    tools = await client.get_tools()
  
    agent = create_agent("gpt-5", tools)
    
    conversation_history = []
    
    print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
    print("Ask any Stormboard related question or task to the agent.\n")
    
    while True:
        user_input = input("You: ").strip()
        
        if user_input.lower() in ['exit', 'quit', 'bye']:
            print("\nGoodbye!")
            break
        
        if not user_input:
            continue
        
        conversation_history.append({"role": "user", "content": user_input})
        print("\nAgent is thinking...\n")
        
        response = await agent.ainvoke({"messages": conversation_history})
        conversation_history = response['messages']
        final_response = response['messages'][-1].content
        print(f"Agent: {final_response}\n")

if __name__ == "__main__":
    asyncio.run(main())

Conclusion

You've successfully built a LangChain agent that can interact with Stormboard through Composio's Tool Router.

Key features of this implementation:

  • Dynamic tool loading through Composio's Tool Router
  • Conversation history maintenance for context-aware responses
  • Async Python provides clean, efficient execution of agent workflows
You can extend this further by adding error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows.

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CrewAI

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Codex

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Use Stormboard MCP with Codex

FAQ

What are the differences in Tool Router MCP and Stormboard MCP?

With a standalone Stormboard MCP server, the agents and LLMs can only access a fixed set of Stormboard tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Stormboard and many other apps based on the task at hand, all through a single MCP endpoint.

Can I use Tool Router MCP with LangChain?

Yes, you can. LangChain fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Stormboard tools.

Can I manage the permissions and scopes for Stormboard while using Tool Router?

Yes, absolutely. You can configure which Stormboard scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

How safe is my data with Composio Tool Router?

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Stormboard data and credentials are handled as safely as possible.

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