How to integrate Fireflies MCP with Mastra AI

Connect Mastra AI to Fireflies MCP. Transcribe this uploaded meeting audio file, summarize your last five recorded calls, and more using natural language, with authentication handled for you.

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Fireflies

Api Key

Fireflies.ai is an AI-powered meeting assistant that records, transcribes, and analyzes voice conversations. It helps teams capture call notes automatically and search or summarize meetings effortlessly.

21 Tools1 Triggers

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Introduction

This guide walks you through connecting Fireflies to Mastra AI using the Composio tool router. By the end, you'll have a working Fireflies agent that can transcribe this uploaded meeting audio file, summarize your last five recorded calls, list all transcripts involving the marketing team through natural language commands.

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

The Fireflies MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Fireflies account. It provides structured and secure access to your meeting transcripts, analytics, participants, topics, channels, user groups, and AskFred conversations, so your agent can search conversations, analyze meetings, review attendance, explore topics, and retrieve AskFred discussions on your behalf.

Transcript search: Have your agent search meeting titles and spoken content for keywords to find relevant conversations.
Meeting insights and analytics: Let the agent review conversation metrics, sentiment, team trends, and individual performance data from your meetings.
Participants and attendance: Direct your agent to retrieve meeting participants and review their attendance details.
Topics and AskFred conversations: Instruct your agent to identify extracted topics, keywords, and meeting types, or retrieve AskFred threads with their full history.
Team organization and roles: Have your agent list accessible channels and user groups, review group membership, or update a team member's role.

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 Fireflies 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 Fireflies

typescript

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

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

What's happening:

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

Create the Mastra agent

typescript

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

  const composioMCPUrl = session.mcp.url;

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

  const composioTools = await mcpClient.getTools();

  const agent = new Agent({
    name: "fireflies-mastra-agent",
    instructions: "You are an AI agent with Fireflies 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: { fireflies: 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 Fireflies 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 & TRIGGERS

Supported Tools and Triggers

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

Add to Live Meeting

The AddToLive Action allows you to add the Fireflies.

Continue AskFred Thread

Tool to continue an existing AskFred conversation thread with follow-up questions.

Create AskFred Thread

Tool to start a new AskFred conversation thread with a question about meetings.

Create Bite

Tool to create a bite (short video or audio clip) from a transcript segment.

Delete Transcript by ID

Permanently delete a transcript from the Fireflies account by its unique ID.

Fetch AI App Outputs

Tool to fetch AI App outputs for specific apps or transcripts.

Get AskFred Thread

Tool to get a specific AskFred conversation thread with full history.

Get AskFred Threads

Tool to retrieve a summary of all AskFred conversation threads for the current user.

Get Bite by ID

Fetches details for a specific bite by ID.

Get Transcripts

Fetches a list of bites (highlights) against input arguments.

Get Transcript by ID

Fetches details for a specific Fireflies transcript ID.

Get Transcripts

Fetches a list of transcripts against input filters.

Get User by ID

The GetUser Action is designed to fetch details associated with a specific user id.

Get User Groups

Tool to fetch a list of all user groups within the team with information about user groups including their members.

Get Users

Fetches a list of all users within the team, including their full email addresses.

Execute GraphQL Query

Execute an authenticated, read-only Fireflies GraphQL operation (query) and return the full raw GraphQL response (data+errors) for reliable fallback and debugging.

Set User Role

Tool to update a user's role within a team.

Update Meeting Channel

Tool to batch update channel assignments for 1-5 meeting transcripts.

Update Meeting Privacy

Tool to update the privacy setting of a meeting transcript.

Update Meeting Title

Tool to update the title of a meeting transcript.

Upload Audio

The UploadAudio Action allows you to upload audio files to Fireflies.

FRAMEWORKS

How to build Fireflies MCP Agent with another framework

Claude Code

Use Fireflies MCP with Claude Code

Cursor

Use Fireflies MCP with Cursor

ChatGPT

Use Fireflies MCP with ChatGPT

Claude Cowork

Use Fireflies MCP with Claude Cowork

Antigravity

Use Fireflies MCP with Antigravity

OpenAI Agents SDK

Use Fireflies MCP with OpenAI Agents SDK

Claude Agent SDK

Use Fireflies MCP with Claude Agent SDK

Codex

Use Fireflies MCP with Codex

Grok Build

Use Fireflies MCP with Grok Build

VS Code

Use Fireflies MCP with VS Code

OpenCode

Use Fireflies MCP with OpenCode

OpenClaw

Use Fireflies MCP with OpenClaw

Hermes

Use Fireflies MCP with Hermes

Atomic Agent

Use Fireflies MCP with Atomic Agent

Google ADK

Use Fireflies MCP with Google ADK

LangChain

Use Fireflies MCP with LangChain

Vercel AI SDK

Use Fireflies MCP with Vercel AI SDK

LlamaIndex

Use Fireflies MCP with LlamaIndex

CrewAI

Use Fireflies MCP with CrewAI

Pydantic AI

Use Fireflies MCP with Pydantic AI

AutoGen

Use Fireflies MCP with AutoGen

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

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

Start with Fireflies.It takes 30 seconds.

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

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How to integrate Fireflies MCP with Mastra AI

Connect Fireflies without auth hassles

Introduction

Also integrate Fireflies with

TL;DR

What is Mastra AI?

What is the Fireflies 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 Fireflies

Configure Mastra MCP client and fetch tools

Create the Mastra agent

Set up interactive chat interface

Complete Code

Conclusion

Supported Tools and Triggers

How to build Fireflies MCP Agent with another framework

Claude Code

Cursor

ChatGPT

Claude Cowork

Antigravity

OpenAI Agents SDK

Claude Agent SDK

Codex

Grok Build

VS Code

OpenCode

OpenClaw

Hermes

Atomic Agent

Google ADK

LangChain

Vercel AI SDK

LlamaIndex

CrewAI

Pydantic AI

AutoGen

Explore Other Toolkits

Firecrawl

Tavily

Exa

Serpapi

Frequently asked questions

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

Can I use Tool Router MCP with Mastra AI?+

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

How safe is my data with Composio Tool Router?+

Start with Fireflies.It takes 30 seconds.