How to integrate Dovetail MCP with Mastra AI

This guide walks you through connecting Dovetail to Mastra AI using the Composio tool router. By the end, you'll have a working Dovetail agent that can summarize all data points for project x, create a new insight from interview notes, list every contact added this month through natural language commands. This guide will help you understand how to give your Mastra AI agent real control over a Dovetail account through Composio's Dovetail MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Dovetail

Api Key

Dovetail is a research analysis platform for transcript review and insight generation. It helps teams code interviews, analyze feedback, and create actionable research summaries.

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Introduction

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

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

Also integrate Dovetail with

OpenAI Agents SDK Claude Agent SDK Claude Code Claude Cowork Codex OpenClaw Hermes CLI Google ADK LangChain Vercel AI SDK LlamaIndex CrewAI

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

The Dovetail MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Dovetail account. It provides structured and secure access to your research workspace, so your agent can perform actions like creating insights, managing contacts, organizing channels, and retrieving research notes on your behalf.

Automated insight creation: Let your agent synthesize findings and store new insights in your Dovetail projects, streamlining your research analysis workflow.
Channel and topic management: Easily create, organize, or delete channels and topics to keep your research data structured and accessible.
Contact management and retrieval: Automatically add new research contacts or list all contacts in your workspace for better respondent tracking.
Research note access: Ask your agent to fetch detailed information about specific notes, giving you instant access to key research materials.
Data point recording and classification: Capture and categorize new data points within channels, ensuring every piece of feedback or observation is logged and ready for analysis.

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:

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

Step-by-step Guide

Step by step09 STEPS

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 Dovetail 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 Dovetail

typescript

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

  const composioMCPUrl = session.mcp.url;
  console.log("Dovetail MCP URL:", composioMCPUrl);

What's happening:

create spins up a short-lived MCP HTTP endpoint for this user
The toolkits array contains "dovetail" for Dovetail 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 Dovetail toolkit

Create the Mastra agent

typescript

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

  const composioMCPUrl = session.mcp.url;

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

  const composioTools = await mcpClient.getTools();

  const agent = new Agent({
    name: "dovetail-mastra-agent",
    instructions: "You are an AI agent with Dovetail 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: { dovetail: 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 Dovetail 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

TOOLS

Supported Tools

Every Dovetail action and event your agent gets out of the box.

Create Channel

Creates a new channel in Dovetail to organize and collect feedback data.

Create Contact

Tool to create a new contact in Dovetail.

Create Data

Tool to create a data item in a Dovetail project with text content, title, and/or structured fields.

Create Data Point

Tool to create a data point within a channel.

Create Doc

Tool to create a doc in a Dovetail project with text content, title and/or custom fields.

Create Insight

Creates a new insight in Dovetail to store synthesized research findings, observations, or conclusions.

Create Note

Tool to create a note in a Dovetail project with text content, title and/or custom fields.

Create Project

Tool to create a new project in your Dovetail workspace.

Create Topic

Tool to create a new topic in a Dovetail channel.

Delete Channel

Tool to delete an existing channel.

Delete Data

Tool to delete an existing data item.

Delete Doc

Tool to delete an existing doc.

Delete Insight

Tool to delete an existing insight.

Delete Note

Tool to delete an existing note.

Delete Topic

Tool to delete an existing topic.

Export Data

Tool to export data in HTML or Markdown format.

Export Doc

Tool to export a doc in HTML or Markdown format.

Export Insight

Tool to export an insight in HTML or Markdown format.

Export Note

Tool to export a note from Dovetail in HTML or Markdown format.

Get Contact

Tool to retrieve details of a specific contact.

Get Data

Tool to retrieve details of a specific data item by ID.

Get Doc

Tool to retrieve details of a specific doc by ID.

Get File

Tool to retrieve details of a specific file by its ID.

Get Folder

Tool to retrieve details of a specific folder.

Get Insight

Tool to retrieve details of a specific insight by ID.

Get Note

Tool to retrieve details of a specific note.

Get Project

Tool to retrieve details of a specific project.

Get Token Info

Retrieves information about the current API token, including its unique identifier and the associated workspace subdomain.

Import Data File

Tool to import a public URL of a file as new data in Dovetail.

Import Doc File

Tool to import a public file URL as a new doc in Dovetail.

Import Insight from File

Tool to import a file from a public URL as a new insight in Dovetail.

Import Note File

Tool to import a file from a public URL as a new note in Dovetail.

List Contacts

Retrieves a paginated list of contacts from a Dovetail workspace.

List Data

Tool to list data items in Dovetail.

List Docs

Tool to list docs in a Dovetail workspace with optional filtering, sorting, and pagination.

List Folders

Tool to get a list of folders associated with a workspace.

List Highlights

List highlights from your Dovetail workspace with optional filtering and pagination.

List Insights

Tool to get a list of insights associated with a workspace.

List Notes

List notes in Dovetail workspace with optional pagination and sorting.

List Projects

Tool to list all projects in Dovetail.

List Tags

List all tags in the authenticated Dovetail workspace.

List User Docs

Tool to get a list of docs associated with a user in Dovetail.

List User Insights

List personal insights for a user in Dovetail.

Magic Search

Tool to perform a magic search across workspace data.

Update Channel

Tool to update an existing channel's title or context.

Update Contact

Tool to update an existing contact in Dovetail.

Update Data

Tool to update a data item in Dovetail.

Update Doc

Tool to update a doc in Dovetail.

Update Insight

Updates an existing insight in Dovetail, allowing you to modify the title and custom fields.

Update Note

Tool to update an existing note in Dovetail.

Update Topic

Tool to update an existing topic.

FRAMEWORKS

How to build Dovetail MCP Agent with another framework

OpenAI Agents SDK

Use Dovetail MCP with OpenAI Agents SDK

Claude Agent SDK

Use Dovetail MCP with Claude Agent SDK

Claude Code

Use Dovetail MCP with Claude Code

Claude Cowork

Use Dovetail MCP with Claude Cowork

Codex

Use Dovetail MCP with Codex

OpenClaw

Use Dovetail MCP with OpenClaw

Hermes

Use Dovetail MCP with Hermes

CLI

Use Dovetail MCP with CLI

Google ADK

Use Dovetail MCP with Google ADK

LangChain

Use Dovetail MCP with LangChain

Vercel AI SDK

Use Dovetail MCP with Vercel AI SDK

LlamaIndex

Use Dovetail MCP with LlamaIndex

CrewAI

Use Dovetail MCP with CrewAI

MORE TOOLKITS

Explore Other Toolkits

Toolkit marketplace

Firecrawl

Api Key

Firecrawl automates large-scale web crawling and data extraction. It helps organizations efficiently gather, index, and analyze content from online sources.

Tavily

Api Key

Tavily offers powerful search and data retrieval from documents, databases, and the web. It helps teams locate and filter information instantly, saving hours on research.

Exa

Api Key

Exa is a data extraction and search platform for gathering and analyzing information from websites, APIs, or databases. It helps teams quickly surface insights and automate data-driven workflows.

Serpapi

Api Key

SerpApi is a real-time API for structured search engine results. It lets you automate SERP data collection, parsing, and analysis for SEO and research.

FAQ

Frequently asked questions

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

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 Dovetail tools.

Yes, absolutely. You can configure which Dovetail 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.

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 Dovetail data and credentials are handled as safely as possible.

Start with Dovetail.It takes 30 seconds.

Managed auth, hosted MCP servers, and every Dovetail tool your agent needs.Free to start.

Start building

Customer stories

Teams ship real agents on Composio

GET STARTED FOR FREE BOOK A DEMO

Karan skipped his own birthday party to fix our critical issue. It was 10pm and he diverted his Waymo to help us instead. This really sets the bar — it shows the commitment you need when users rely on your software.

Harsha Gaddipati

Co-founder, Slashy

A lot of students tell us that the moment their connected tools start talking to each other inside Opennote feels almost magical. The agent just knows them, and it's immensely helped keep new users on the platform.

Abhi Arya

Co-founder, Opennote

We chose Composio over Pipedream because it delivered depth where it mattered — niche tools and tricky edge cases other platforms simply ignored. That gave us confidence to scale without compromising.

Nirman Dave

CEO, Zams

As a solo builder, shipping fast is life or death. The only way I can outcompete incumbents is by outmanoeuvring them. Getting bogged down managing agent auth would have been a death sentence.

Ryan Yu

Founder, Extra Thursday

Before Composio, adding tool integrations was slow and resource-intensive. Each one could take weeks of engineering time, and maintaining them meant constantly keeping up with API changes.

Tomisin Jenrola

Founder & CEO, SwarmZero

With hands-on help from their founder, we integrated Gmail and Google Drive in just 30 minutes. This level of personal support and commitment is exactly what startups should strive for.

Jerome Leclanche

Co-Founder, Ingram Technologies

How to integrate Dovetail MCP with Mastra AI

Connect Dovetail without auth hassles

Introduction

Also integrate Dovetail with

TL;DR

What is Mastra AI?

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

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

What is Composio SDK?

How the Composio SDK works

Step-by-step Guide

Prerequisites

Getting API Keys for OpenAI and Composio

Install dependencies

Set up environment variables

Import libraries and validate environment

Create a Tool Router session for Dovetail

Configure Mastra MCP client and fetch tools

Create the Mastra agent

Set up interactive chat interface

Complete Code

Conclusion

Supported Tools

How to build Dovetail MCP Agent with another framework

OpenAI Agents SDK

Claude Agent SDK

Claude Code

Claude Cowork

Codex

OpenClaw

Hermes

CLI

Google ADK

LangChain

Vercel AI SDK

LlamaIndex

CrewAI

Explore Other Toolkits

Firecrawl

Tavily

Exa

Serpapi

Frequently asked questions

What are the differences in Tool Router MCP and Dovetail MCP?+

Can I use Tool Router MCP with Mastra AI?+

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

How safe is my data with Composio Tool Router?+

Start with Dovetail.It takes 30 seconds.

Teams ship real agents on Composio