How to integrate Klipfolio MCP with Mastra AI

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Introduction

This guide walks you through connecting Klipfolio to Mastra AI using the Composio tool router. By the end, you'll have a working Klipfolio agent that can create a new dashboard for marketing kpis, list all available data sources in your account, append this week's sales csv to data source through natural language commands.

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

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

Also integrate Klipfolio with

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 Klipfolio tools
  • Connect Mastra's MCP client to the Composio generated MCP URL
  • Fetch Klipfolio 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 Klipfolio 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 Klipfolio MCP server, and what's possible with it?

The Klipfolio MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Klipfolio account. It provides structured and secure access to your dashboards and data sources, so your agent can perform actions like creating dashboards, updating data sources, retrieving analytics, and managing visualizations on your behalf.

  • Effortless dashboard creation and management: Ask your agent to create new dashboards (tabs), organize visualizations, or fetch detailed information about existing dashboards for instant business insights.
  • Comprehensive data source handling: Let your agent list, create, refresh, or delete data sources, ensuring your reports are always up to date and data flows smoothly.
  • Automated data updating: Instruct your agent to append fresh data to data sources or trigger refreshes across multiple sources simultaneously, keeping analytics current without manual effort.
  • Visualization and klip management: Retrieve a list of all your klips (visual components), enabling your agent to analyze, summarize, or reference the data visualizations you rely on most.
  • User profile and account verification: Have the agent check authentication or pull user profile details, helping you audit access and monitor account activity with ease.

Supported Tools & Triggers

Tools
Assign User RoleTool to assign a role to a user in Klipfolio.
Create Data SourceThis tool creates a new data source in Klipfolio.
Create Data Source InstanceTool to create a new data source instance based on an existing data source in Klipfolio.
Create GroupTool to create a new group in Klipfolio.
Create RoleTool to create a new role in Klipfolio with optional permissions.
Create Tab (Dashboard)This tool creates a new tab (dashboard) in Klipfolio.
Create UserTool to create a new user in Klipfolio with optional roles and client association.
Delete Data SourceThis tool permanently removes a specified data source from the Klipfolio account.
Delete Data Source Instance PropertyTool to delete a property from a data source instance in Klipfolio.
Delete Data Source PropertyTool to delete a property from a data source in Klipfolio.
Delete Data Source Share RightTool to delete a data source share right for a specific user or group.
Delete GroupTool to permanently delete a specified group from the Klipfolio account.
Delete RoleTool to delete a role from Klipfolio.
Disable Data SourceTool to disable a data source in Klipfolio.
Enable Data SourceTool to enable a disabled data source in Klipfolio.
Get Dashboard DetailsThis tool retrieves detailed information about a specific dashboard (formerly known as tab) in Klipfolio.
Get Data Source DetailsTool to retrieve detailed information about a specific data source in Klipfolio.
Get Data Source Instance DetailsTool to retrieve detailed information about a specific data source instance in Klipfolio.
Get Data Source Instance DataTool to retrieve the actual data from a specific data source instance in Klipfolio.
Get Data Source Instance PropertiesTool to retrieve configuration properties for a specific data source instance in Klipfolio.
Get Data Source PropertiesTool to retrieve properties for a specific data source in Klipfolio by its ID.
Get Data Source Share RightsTool to retrieve sharing permissions for a specific data source in Klipfolio.
Get Group DetailsTool to retrieve detailed information about a specific group in Klipfolio.
Get Group Default TabsTool to retrieve the list of default tabs (dashboards) for a specific group.
Get Group UsersTool to retrieve all users belonging to a specific group in Klipfolio.
Get KlipsThis tool retrieves a list of all Klips accessible to the authenticated user.
Get User ProfileThis tool is used to retrieve the authenticated user's profile information and test the authentication status.
Get Role DetailsTool to retrieve detailed information about a specific role in Klipfolio.
Get Role PermissionsTool to retrieve the list of permissions assigned to a specific role in Klipfolio.
Get Role UsersTool to retrieve all users associated with a specific role in Klipfolio.
Get User DetailsTool to retrieve detailed information about a specific user in Klipfolio.
Get User GroupsTool to retrieve all groups that a specific user belongs to in Klipfolio.
Get User PropertiesTool to retrieve custom properties associated with a specific user in Klipfolio.
Get User RolesTool to retrieve all roles assigned to a specific user in Klipfolio.
Get User Tab InstancesTool to retrieve all tab instances associated with a specific user.
List Data Source InstancesTool to retrieve all data source instances accessible to the authenticated user.
List All Data SourcesThis tool retrieves a list of all data sources associated with an authenticated Klipfolio account.
List All GroupsTool to retrieve all groups from a Klipfolio account.
List All RolesTool to retrieve all roles in the company.
List All UsersTool to retrieve all users in the company.
Refresh Data Source InstanceTool to manually refresh a data source instance in Klipfolio.
Refresh Multiple Data SourcesThis tool allows users to refresh multiple data sources in Klipfolio simultaneously.
Resend User InviteTool to resend a user invitation email in Klipfolio.
Reset User PasswordTool to reset a user's password in Klipfolio.
Update Data SourceThis tool allows you to replace/update the data in an existing Klipfolio data source.
Update Data Source Instance PropertiesTool to update custom properties on a Klipfolio data source instance.
Update Data Source MetadataTool to update metadata (name, description, refresh_interval) of an existing data source.
Update Data Source PropertiesTool to update custom properties for a data source in Klipfolio.
Update Data Source Share RightsTool to update data source share rights in Klipfolio.
Update User PropertiesTool to update custom properties for a user in Klipfolio.

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

What is Composio SDK?

Composio's Composio SDK 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 Composio SDK

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

How the Composio SDK works

The Composio SDK 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 Klipfolio 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 Klipfolio

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

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

Create the Mastra agent

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

  const composioMCPUrl = session.mcp.url;

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

  const composioTools = await mcpClient.getTools();

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

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FAQ

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

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

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

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

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