How to integrate Stormboard MCP with Mastra AI

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Introduction

This guide walks you through connecting Stormboard to Mastra AI 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 Mastra AI 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:
  • Set up your environment so Mastra, OpenAI, and Composio work together
  • Create a Tool Router session in Composio that exposes Stormboard tools
  • Connect Mastra's MCP client to the Composio generated MCP URL
  • Fetch Stormboard tool definitions and attach them as a toolset
  • Build a Mastra agent that can reason, call tools, and return structured results
  • Run an interactive CLI where you can chat with your Stormboard agent

What is Mastra AI?

Mastra AI is a TypeScript framework for building AI agents with tool support. It provides a clean API for creating agents that can use external services through MCP.

Key features include:

  • MCP Client: Built-in support for Model Context Protocol servers
  • Toolsets: Organize tools into logical groups
  • Step Callbacks: Monitor and debug agent execution
  • OpenAI Integration: Works with OpenAI models via @ai-sdk/openai

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, make sure you have:
  • Node.js 18 or higher
  • A Composio account with an active API key
  • An OpenAI API key
  • Basic familiarity with TypeScript

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key.
  • You need credits or a connected billing setup to use the models.
  • Store the key somewhere safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Go to Settings and copy your API key.
  • This key lets your Mastra agent talk to Composio and reach Stormboard through MCP.

Install dependencies

bash
npm install @composio/core @mastra/core @mastra/mcp @ai-sdk/openai dotenv

Install the required packages.

What's happening:

  • @composio/core is the Composio SDK for creating MCP sessions
  • @mastra/core provides the Agent class
  • @mastra/mcp is Mastra's MCP client
  • @ai-sdk/openai is the model wrapper for OpenAI
  • dotenv loads environment variables from .env

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_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
  • COMPOSIO_USER_ID tells Composio which user this session belongs to
  • OPENAI_API_KEY lets the Mastra agent call OpenAI models

Import libraries and validate environment

typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Agent } from "@mastra/core/agent";
import { MCPClient } from "@mastra/mcp";
import { Composio } from "@composio/core";
import * as readline from "readline";

import type { AiMessageType } from "@mastra/core/agent";

const openaiAPIKey = process.env.OPENAI_API_KEY;
const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!openaiAPIKey) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({
  apiKey: composioAPIKey as string,
});
What's happening:
  • dotenv/config auto loads your .env so process.env.* is available
  • openai gives you a Mastra compatible model wrapper
  • Agent is the Mastra agent that will call tools and produce answers
  • MCPClient connects Mastra to your Composio MCP server
  • Composio is used to create a Tool Router session

Create a Tool Router session for Stormboard

typescript
async function main() {
  const session = await composio.create(
    composioUserID as string,
    {
      toolkits: ["stormboard"],
    },
  );

  const composioMCPUrl = session.mcp.url;
  console.log("Stormboard MCP URL:", composioMCPUrl);
What's happening:
  • create spins up a short-lived MCP HTTP endpoint for this user
  • The toolkits array contains "stormboard" for Stormboard access
  • session.mcp.url is the MCP URL that Mastra's MCPClient will connect to

Configure Mastra MCP client and fetch tools

typescript
const mcpClient = new MCPClient({
    id: composioUserID as string,
    servers: {
      nasdaq: {
        url: new URL(composioMCPUrl),
        requestInit: {
          headers: session.mcp.headers,
        },
      },
    },
    timeout: 30_000,
  });

console.log("Fetching MCP tools from Composio...");
const composioTools = await mcpClient.getTools();
console.log("Number of tools:", Object.keys(composioTools).length);
What's happening:
  • MCPClient takes an id for this client and a list of MCP servers
  • The headers property includes the x-api-key for authentication
  • getTools fetches the tool definitions exposed by the Stormboard toolkit

Create the Mastra agent

typescript
const agent = new Agent({
    name: "stormboard-mastra-agent",
    instructions: "You are an AI agent with Stormboard tools via Composio.",
    model: "openai/gpt-5",
  });
What's happening:
  • Agent is the core Mastra agent
  • name is just an identifier for logging and debugging
  • instructions guide the agent to use tools instead of only answering in natural language
  • model uses openai("gpt-5") to configure the underlying LLM

Set up interactive chat interface

typescript
let messages: AiMessageType[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end.\n");

const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
  prompt: "> ",
});

rl.prompt();

rl.on("line", async (userInput: string) => {
  const trimmedInput = userInput.trim();

  if (["exit", "quit", "bye"].includes(trimmedInput.toLowerCase())) {
    console.log("\nGoodbye!");
    rl.close();
    process.exit(0);
  }

  if (!trimmedInput) {
    rl.prompt();
    return;
  }

  messages.push({
    id: crypto.randomUUID(),
    role: "user",
    content: trimmedInput,
  });

  console.log("\nAgent is thinking...\n");

  try {
    const response = await agent.generate(messages, {
      toolsets: {
        stormboard: composioTools,
      },
      maxSteps: 8,
    });

    const { text } = response;

    if (text && text.trim().length > 0) {
      console.log(`Agent: ${text}\n`);
        messages.push({
          id: crypto.randomUUID(),
          role: "assistant",
          content: text,
        });
      }
    } catch (error) {
      console.error("\nError:", error);
    }

    rl.prompt();
  });

  rl.on("close", async () => {
    console.log("\nSession ended.");
    await mcpClient.disconnect();
    process.exit(0);
  });
}

main().catch((err) => {
  console.error("Fatal error:", err);
  process.exit(1);
});
What's happening:
  • messages keeps the full conversation history in Mastra's expected format
  • agent.generate runs the agent with conversation history and Stormboard toolsets
  • maxSteps limits how many tool calls the agent can take in a single run
  • onStepFinish is a hook that prints intermediate steps for debugging

Complete Code

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

typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Agent } from "@mastra/core/agent";
import { MCPClient } from "@mastra/mcp";
import { Composio } from "@composio/core";
import * as readline from "readline";

import type { AiMessageType } from "@mastra/core/agent";

const openaiAPIKey = process.env.OPENAI_API_KEY;
const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!openaiAPIKey) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({ apiKey: composioAPIKey as string });

async function main() {
  const session = await composio.create(composioUserID as string, {
    toolkits: ["stormboard"],
  });

  const composioMCPUrl = session.mcp.url;

  const mcpClient = new MCPClient({
    id: composioUserID as string,
    servers: {
      stormboard: {
        url: new URL(composioMCPUrl),
        requestInit: {
          headers: session.mcp.headers,
        },
      },
    },
    timeout: 30_000,
  });

  const composioTools = await mcpClient.getTools();

  const agent = new Agent({
    name: "stormboard-mastra-agent",
    instructions: "You are an AI agent with Stormboard tools via Composio.",
    model: "openai/gpt-5",
  });

  let messages: AiMessageType[] = [];

  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: "> ",
  });

  rl.prompt();

  rl.on("line", async (input: string) => {
    const trimmed = input.trim();
    if (["exit", "quit"].includes(trimmed.toLowerCase())) {
      rl.close();
      return;
    }

    messages.push({ id: crypto.randomUUID(), role: "user", content: trimmed });

    const { text } = await agent.generate(messages, {
      toolsets: { stormboard: composioTools },
      maxSteps: 8,
    });

    if (text) {
      console.log(`Agent: ${text}\n`);
      messages.push({ id: crypto.randomUUID(), role: "assistant", content: text });
    }

    rl.prompt();
  });

  rl.on("close", async () => {
    await mcpClient.disconnect();
    process.exit(0);
  });
}

main();

Conclusion

You've built a Mastra AI agent that can interact with Stormboard through Composio's Tool Router. You can extend this further by:
  • Adding other toolkits like Gmail, Slack, or GitHub
  • Building a web-based chat interface around this agent
  • Using multiple MCP endpoints to enable cross-app workflows

How to build Stormboard MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Stormboard MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Stormboard MCP with Claude Agent SDK

Google ADK

Google ADK

Use Stormboard MCP with Google ADK

LangChain

LangChain

Use Stormboard MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Stormboard MCP with Vercel AI SDK

LlamaIndex

LlamaIndex

Use Stormboard MCP with LlamaIndex

CrewAI

CrewAI

Use Stormboard MCP with CrewAI

Claude Code

Claude Code

Use Stormboard MCP with Claude Code

Codex

Codex

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 Mastra AI?

Yes, you can. Mastra AI 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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