How to integrate Dovetail MCP with OpenAI Agents SDK

This guide walks you through connecting Dovetail to the OpenAI Agents SDK 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 OpenAI Agents SDK 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 is a research analysis platform for transcript review and insight generation. It helps teams code interviews, analyze feedback, and create actionable research summaries.

51 Tools

Introduction

This guide walks you through connecting Dovetail to the OpenAI Agents SDK 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 OpenAI Agents SDK 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

Claude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAI

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Install the necessary dependencies
  • Initialize Composio and create a Tool Router session for Dovetail
  • Configure an AI agent that can use Dovetail as a tool
  • Run a live chat session where you can ask the agent to perform Dovetail operations

What is OpenAI Agents SDK?

The OpenAI Agents SDK is a lightweight framework for building AI agents that can use tools and maintain conversation state. It provides a simple interface for creating agents with hosted MCP tool support.

Key features include:

  • Hosted MCP Tools: Connect to external services through hosted MCP endpoints
  • SQLite Sessions: Persist conversation history across interactions
  • Simple API: Clean interface with Agent, Runner, and tool configuration
  • Streaming Support: Real-time response streaming for interactive applications

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:

  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

Step by step09 STEPS
1

Prerequisites

Before starting, make sure you have:
  • Composio API Key and OpenAI API Key
  • Primary know-how of OpenAI Agents SDK
  • A live Dovetail project
  • Some knowledge of Python or Typescript
2

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
3

Install dependencies

npm install @composio/openai-agents @openai/agents dotenv

Install the Composio SDK and the OpenAI Agents SDK.

4

Set up environment variables

bash
OPENAI_API_KEY=sk-...your-api-key
COMPOSIO_API_KEY=your-api-key
USER_ID=composio_user@gmail.com

Create a .env file and add your OpenAI and Composio API keys.

5

Import dependencies

import 'dotenv/config';
import { Composio } from '@composio/core';
import { OpenAIAgentsProvider } from '@composio/openai-agents';
import { Agent, hostedMcpTool, run, OpenAIConversationsSession } from '@openai/agents';
import * as readline from 'readline';
What's happening:
  • You're importing all necessary libraries.
  • The Composio and OpenAIAgentsProvider classes are imported to connect your OpenAI agent to Composio tools like Dovetail.
6

Set up the Composio instance

dotenv.config();

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.USER_ID;

if (!composioApiKey) {
  throw new Error('COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key');
}
if (!userId) {
  throw new Error('USER_ID is not set');
}

// Initialize Composio
const composio = new Composio({
  apiKey: composioApiKey,
  provider: new OpenAIAgentsProvider(),
});
What's happening:
  • dotenv.config() loads your .env file so COMPOSIO_API_KEY and USER_ID are available as environment variables.
  • Creating a Composio instance using the API Key and OpenAIAgentsProvider class.
7

Create a Tool Router session

// Create Tool Router session for Dovetail
const session = await composio.create(userId as string, {
  toolkits: ['dovetail'],
});
const mcpUrl = session.mcp.url;

What is happening:

  • You give the Tool Router the user id and the toolkits you want available. Here, it is only dovetail.
  • The router checks the user's Dovetail connection and prepares the MCP endpoint.
  • The returned session.mcp.url is the MCP URL that your agent will use to access Dovetail.
  • This approach keeps things lightweight and lets the agent request Dovetail tools only when needed during the conversation.
8

Configure the agent

// Configure agent with MCP tool
const agent = new Agent({
  name: 'Assistant',
  model: 'gpt-5',
  instructions:
    'You are a helpful assistant that can access Dovetail. Help users perform Dovetail operations through natural language.',
  tools: [
    hostedMcpTool({
      serverLabel: 'tool_router',
      serverUrl: mcpUrl,
      headers: { 'x-api-key': composioApiKey },
      requireApproval: 'never',
    }),
  ],
});
What's happening:
  • We're creating an Agent instance with a name, model (gpt-5), and clear instructions about its purpose.
  • The agent's instructions tell it that it can access Dovetail and help with queries, inserts, updates, authentication, and fetching database information.
  • The tools array includes a hostedMcpTool that connects to the MCP server URL we created earlier.
  • The headers object includes the Composio API key for secure authentication with the MCP server.
  • requireApproval: 'never' means the agent can execute Dovetail operations without asking for permission each time, making interactions smoother.
9

Start chat loop and handle conversation

// Keep conversation state across turns
const conversationSession = new OpenAIConversationsSession();

// Simple CLI
const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
  prompt: 'You: ',
});

console.log('\nComposio Tool Router session created.');
console.log('\nChat started. Type your requests below.');
console.log("Commands: 'exit', 'quit', or 'q' to end\n");

try {
  const first = await run(agent, 'What can you help me with?', { session: conversationSession });
  console.log(`Assistant: ${first.finalOutput}\n`);
} catch (e) {
  console.error('Error:', e instanceof Error ? e.message : e, '\n');
}

rl.prompt();

rl.on('line', async (userInput) => {
  const text = userInput.trim();

  if (['exit', 'quit', 'q'].includes(text.toLowerCase())) {
    console.log('Goodbye!');
    rl.close();
    process.exit(0);
  }

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

  try {
    const result = await run(agent, text, { session: conversationSession });
    console.log(`\nAssistant: ${result.finalOutput}\n`);
  } catch (e) {
    console.error('Error:', e instanceof Error ? e.message : e, '\n');
  }

  rl.prompt();
});

rl.on('close', () => {
  console.log('\n👋 Session ended.');
  process.exit(0);
});
What's happening:
  • The program prints a session URL that you visit to authorize Dovetail.
  • After authorization, the chat begins.
  • Each message you type is processed by the agent using run().
  • The responses are printed to the console.
  • Typing exit, quit, or q cleanly ends the chat.

Complete Code

Here's the complete code to get you started with Dovetail and OpenAI Agents SDK:

import 'dotenv/config';
import { Composio } from '@composio/core';
import { OpenAIAgentsProvider } from '@composio/openai-agents';
import { Agent, hostedMcpTool, run, OpenAIConversationsSession } from '@openai/agents';
import * as readline from 'readline';

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.USER_ID;

if (!composioApiKey) {
  throw new Error('COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key');
}
if (!userId) {
  throw new Error('USER_ID is not set');
}

// Initialize Composio
const composio = new Composio({
  apiKey: composioApiKey,
  provider: new OpenAIAgentsProvider(),
});

async function main() {
  // Create Tool Router session
  const session = await composio.create(userId as string, {
    toolkits: ['dovetail'],
  });
  const mcpUrl = session.mcp.url;

  // Configure agent with MCP tool
  const agent = new Agent({
    name: 'Assistant',
    model: 'gpt-5',
    instructions:
      'You are a helpful assistant that can access Dovetail. Help users perform Dovetail operations through natural language.',
    tools: [
      hostedMcpTool({
        serverLabel: 'tool_router',
        serverUrl: mcpUrl,
        headers: { 'x-api-key': composioApiKey },
        requireApproval: 'never',
      }),
    ],
  });

  // Keep conversation state across turns
  const conversationSession = new OpenAIConversationsSession();

  // Simple CLI
  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: ',
  });

  console.log('\nComposio Tool Router session created.');
  console.log('\nChat started. Type your requests below.');
  console.log("Commands: 'exit', 'quit', or 'q' to end\n");

  try {
    const first = await run(agent, 'What can you help me with?', { session: conversationSession });
    console.log(`Assistant: ${first.finalOutput}\n`);
  } catch (e) {
    console.error('Error:', e instanceof Error ? e.message : e, '\n');
  }

  rl.prompt();

  rl.on('line', async (userInput) => {
    const text = userInput.trim();

    if (['exit', 'quit', 'q'].includes(text.toLowerCase())) {
      console.log('Goodbye!');
      rl.close();
      process.exit(0);
    }

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

    try {
      const result = await run(agent, text, { session: conversationSession });
      console.log(`\nAssistant: ${result.finalOutput}\n`);
    } catch (e) {
      console.error('Error:', e instanceof Error ? e.message : e, '\n');
    }

    rl.prompt();
  });

  rl.on('close', () => {
    console.log('\nSession ended.');
    process.exit(0);
  });
}

main().catch((err) => {
  console.error('Fatal error:', err);
  process.exit(1);
});

Conclusion

This was a starter code for integrating Dovetail MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Dovetail.

Key features:

  • Hosted MCP tool integration through Composio's Tool Router
  • SQLite session persistence for conversation history
  • Simple async chat loop for interactive testing
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.
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

Claude Agent SDK logo

Claude Agent SDK

Use Dovetail MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Dovetail MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Dovetail MCP with Claude Cowork

Codex logo

Codex

Use Dovetail MCP with Codex

OpenClaw logo

OpenClaw

Use Dovetail MCP with OpenClaw

Hermes logo

Hermes

Use Dovetail MCP with Hermes

CLI logo

CLI

Use Dovetail MCP with CLI

Google ADK logo

Google ADK

Use Dovetail MCP with Google ADK

LangChain logo

LangChain

Use Dovetail MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Dovetail MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Dovetail MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Dovetail MCP with LlamaIndex

CrewAI logo

CrewAI

Use Dovetail MCP with CrewAI

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. OpenAI Agents SDK 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.

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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.

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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.

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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
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.

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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.

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Jerome Leclanche
Co-Founder, Ingram Technologies