How to integrate Rocketlane MCP with Mastra AI

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Introduction

This guide walks you through connecting Rocketlane to Mastra AI using the Composio tool router. By the end, you'll have a working Rocketlane agent that can create a new onboarding project for acme corp, log two hours to client implementation task, archive completed projects from last quarter, get detailed info for company with id 12345 through natural language commands.

This guide will help you understand how to give your Mastra AI agent real control over a Rocketlane account through Composio's Rocketlane 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 Rocketlane tools
  • Connect Mastra's MCP client to the Composio generated MCP URL
  • Fetch Rocketlane 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 Rocketlane 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 Rocketlane MCP server, and what's possible with it?

The Rocketlane MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Rocketlane account. It provides structured and secure access to your onboarding projects, tasks, and customer data, so your agent can perform actions like creating tasks, managing companies, tracking time entries, and handling project organization on your behalf.

  • Project and company management: Easily direct your agent to create new projects or companies, retrieve detailed company info, and keep your workspace organized.
  • Task creation and deletion: Have your agent add new tasks to any project or swiftly delete outdated tasks using their unique identifiers.
  • Time entry tracking: Log time spent on tasks or projects, review details, or delete time entries for accurate billing and reporting.
  • Custom field insights: Retrieve all available custom fields or fetch specific field details to tailor onboarding workflows to your needs.
  • Project archiving and cleanup: Archive completed projects for future reference or permanently delete projects when they're no longer needed, keeping your workspace tidy.

Supported Tools & Triggers

Tools
Archive Project by IDArchives a specific project based on its unique identifier.
Create CompanyCreates a new company (account) in rocketlane.
Create TaskCreates a new task.
Create Time EntryTool to create a new time entry in rocketlane.
Delete ProjectThis tool allows users to permanently delete a project in rocketlane.
Delete Task By IDDelete a specific task using its unique identifier (taskid).
Delete Time Entry by IDDelete a specific time entry using its unique identifier (timeentryid).
Get All FieldsRetrieve all custom fields available in the system.
Get CompanyThis tool retrieves detailed information about a specific company/account in rocketlane by its id.
Get Field By IDRetrieve detailed information about a specific custom field using its unique identifier (fieldid).
Get Project by IDRetrieves detailed information about a specific project using its unique identifier.
Get Task By IdRetrieve extensive information about a specific task using the task's unique identifier (taskid).
Get Template By IDRetrieve detailed information about a specific template using its unique identifier (templateid).
Get Time EntriesTool to retrieve all time entries from rocketlane.
Get Time Entry By IDRetrieve detailed information about a specific time entry using its unique identifier (timeentryid).
Get User By IDRetrieve detailed information about a specific user using their unique identifier (userid).
List CompaniesThis tool retrieves a list of all companies/accounts in rocketlane.
List Company FieldsThis tool retrieves a list of all available company/account fields in rocketlane.
List Company Note FieldsThis tool retrieves a list of all available note fields for companies in rocketlane.
List CurrenciesReturns a predefined list of commonly used currencies since rocketlane api doesn't provide a dedicated currencies endpoint.
List Customer UsersList customer users.
List Project FieldsThis tool retrieves a list of all project fields in rocketlane, including both default and custom fields.
List Project PhasesThis tool retrieves a list of project phases from rocketlane.
List ProjectsThis tool retrieves a list of all projects in the rocketlane instance.
List Task FieldsThis tool retrieves a list of all task fields in rocketlane.
List TemplatesThis tool retrieves a list of all available templates in rocketlane.
List UsersThis tool retrieves all users in the rocketlane instance.
List Vendor UsersList vendor users by filtering users with type 'partner'.
Retrieve Subscription DetailsRetrieves detailed information about the current subscription.
Search User By EmailSearch user by email id.
Update CompanyThis tool updates an existing company/account in rocketlane.
Update Project By IdUpdates an existing project's details using its unique identifier.
Update Time Entry by IDUpdate existing time entry details using its unique identifier (timeentryid).

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 Rocketlane 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 Rocketlane

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

  const composioMCPUrl = session.mcp.url;
  console.log("Rocketlane MCP URL:", composioMCPUrl);
What's happening:
  • create spins up a short-lived MCP HTTP endpoint for this user
  • The toolkits array contains "rocketlane" for Rocketlane 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 Rocketlane toolkit

Create the Mastra agent

typescript
const agent = new Agent({
    name: "rocketlane-mastra-agent",
    instructions: "You are an AI agent with Rocketlane 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: {
        rocketlane: 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 Rocketlane 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 Rocketlane 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: ["rocketlane"],
  });

  const composioMCPUrl = session.mcp.url;

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

  const composioTools = await mcpClient.getTools();

  const agent = new Agent({
    name: "rocketlane-mastra-agent",
    instructions: "You are an AI agent with Rocketlane 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: { rocketlane: 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 Rocketlane 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 Rocketlane MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Rocketlane MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Rocketlane MCP with Claude Agent SDK

Google ADK

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Use Rocketlane MCP with Google ADK

LangChain

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Use Rocketlane MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Rocketlane MCP with Vercel AI SDK

LlamaIndex

LlamaIndex

Use Rocketlane MCP with LlamaIndex

CrewAI

CrewAI

Use Rocketlane MCP with CrewAI

FAQ

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

With a standalone Rocketlane MCP server, the agents and LLMs can only access a fixed set of Rocketlane tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Rocketlane 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 Rocketlane tools.

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

Yes, absolutely. You can configure which Rocketlane 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 Rocketlane data and credentials are handled as safely as possible.

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