How to integrate Recallai MCP with CrewAI

Trusted by
AWS
Glean
Zoom
Airtable

30 min · no commitment · see it on your stack

Recallai logo
CrewAI logo
divider

Introduction

This guide walks you through connecting Recallai to CrewAI using the Composio tool router. By the end, you'll have a working Recallai agent that can start recording your zoom meeting now, list all bots active in meetings, retrieve chat messages from today's calls through natural language commands.

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

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

Also integrate Recallai with

TL;DR

Here's what you'll learn:
  • Get a Composio API key and configure your Recallai connection
  • Set up CrewAI with an MCP enabled agent
  • Create a Tool Router session or standalone MCP server for Recallai
  • Build a conversational loop where your agent can execute Recallai operations

What is CrewAI?

CrewAI is a powerful framework for building multi-agent AI systems. It provides primitives for defining agents with specific roles, creating tasks, and orchestrating workflows through crews.

Key features include:

  • Agent Roles: Define specialized agents with specific goals and backstories
  • Task Management: Create tasks with clear descriptions and expected outputs
  • Crew Orchestration: Combine agents and tasks into collaborative workflows
  • MCP Integration: Connect to external tools through Model Context Protocol

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

The Recallai MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Recallai account. It provides structured and secure access to your meeting bots and conversation data, so your agent can create bots, manage recordings, retrieve chat messages, and orchestrate meeting participation on your behalf.

  • Automated bot creation and management: Quickly spin up new meeting bots, retrieve details, and remove bots as needed for your meetings.
  • Meeting recording control: Let your agent start or stop recordings during live calls, ensuring you capture the most important moments hands-free.
  • Chat message retrieval: Effortlessly access and analyze chat messages exchanged during meetings, enabling summaries or follow-up actions.
  • Bot participation orchestration: Seamlessly remove bots from calls when their job is done, keeping your meetings efficient and secure.
  • Comprehensive bot listing and oversight: View and manage all active bots connected to your Recallai account for smooth operations and tracking.

Supported Tools & Triggers

Tools
Create botCreate a new bot to join and record a meeting.
Create Calendar IntegrationTool to create a new calendar integration with Google Calendar or Microsoft Outlook.
Create Calendar Authentication TokenTool to generate an authentication token for calendar APIs, scoped to the user.
Create Google LoginTool to create a new Google Login credential within a login group.
Create Google Login GroupTool to create a new Google Login Group for managing bot authentication.
Create Meeting Direct ConnectTool to create a Meeting Direct Connect for Google Meet or Zoom.
Create SDK UploadCreate a new Desktop SDK upload.
Create Zoom OAuth AppTool to create a new Zoom OAuth App integration with Recall.
Delete botDelete a scheduled bot by ID.
Delete Bot MediaDeletes bot media stored by Recall AI.
Delete calendarDelete a calendar by ID.
Delete Calendar UserDelete calendar user and disconnect any connected calendars.
Destroy Google LoginTool to delete an existing Google Login by ID.
Destroy Google Login GroupTool to delete an existing Google Login Group by ID.
Destroy Zoom OAuth AppTool to delete a Zoom OAuth App by ID.
Disconnect Calendar UserTool to disconnect a calendar platform (Google or Microsoft) from the user's Recall.
List audio mixedList audio mixed artifacts from Recall.
List Audio SeparateList audio separation artifacts from recordings.
List botsList all bots in your Recall.
List Bot ScreenshotsList all screenshots captured by a bot during a meeting.
List Calendar EventsGet a list of calendar events from connected calendars.
List calendar meetingsList all calendar meetings for the authenticated calendar user.
List calendarsTool to retrieve a list of calendars integrated with Recall.
List calendar usersList all calendar users created for the account.
List chat messagesGet list of chat messages read by the bot in the meeting(excluding messages sent by the bot itself).
List Google Login GroupsTool to retrieve a list of all Google Login Groups in your Recall.
List Google LoginsTool to retrieve a list of all Google Logins in your Recall.
List Meeting Direct ConnectsList all Meeting Direct Connect instances in your Recall.
List Meeting MetadataList meeting metadata from Recall.
List participant eventsList participant events artifacts from recorded meetings.
List Realtime EndpointsTool to list realtime endpoints from Recall.
List RecordingsTool to list recordings from Recall.
List Desktop SDK UploadsTool to get a paginated list of all Desktop SDK uploads in your Recall.
List Slack TeamsTool to list all Slack team integrations.
List transcriptTool to list transcripts from Recall.
List Video Mixed ArtifactsList video mixed artifacts from recorded meetings.
List video separateList video separate artifacts from Recall.
List zoom meetings to credentialsTool to retrieve mappings from Zoom Meeting IDs to Zoom OAuth Credentials.
List Zoom OAuth App LogsTool to retrieve Zoom OAuth app logs from Recall.
List Zoom OAuth AppsTool to retrieve a list of Zoom OAuth apps configured in Recall.
List Zoom OAuth Credential LogsTool to retrieve all Zoom OAuth Credential logs from Recall.
List Zoom OAuth CredentialsTool to retrieve a list of all Zoom OAuth credentials in your Recall.
Remove bot from callRemoves the bot from the meeting call.
Retrieve Billing UsageRetrieve bot usage statistics for billing purposes.
Retrieve botRetrieve detailed information about a specific bot instance by its ID.
Retrieve calendarsRetrieve detailed information about a specific calendar by its UUID.
Retrieve Google Login GroupTool to retrieve an existing Google Login Group by its ID.
Retrieve Meeting Direct ConnectTool to retrieve detailed information about a Meeting Direct Connect instance by its ID.
Retrieve recordingTool to retrieve detailed information about a specific recording by its UUID.
Retrieve sdk uploadRetrieve detailed information about a Desktop SDK upload instance by its ID.
Retrieve Video MixedRetrieve a video mixed artifact by its ID.
Retrieve Zoom OAuth AppRetrieve detailed information about a specific Zoom OAuth app by its ID.
Start recordingInstructs the bot to start recording the meeting.
Stop recordingStops the current recording for the specified bot.
Update BotTool to partially update a scheduled bot.
Update CalendarUpdate an existing calendar integration in Recall.
Update Calendar UserUpdate recording preferences and calendar connections for a calendar user.
Update Google LoginTool to update an existing Google Login credential.
Update Google Login GroupTool to update an existing Google Login Group in Recall.
Partial Update Google Login GroupTool to partially update an existing Google Login Group in Recall.
Update RecordingTool to update a recording's metadata.
Update Video MixedTool to partially update a video mixed artifact by ID.
Update Zoom OAuth AppTool to update an existing Zoom OAuth App's credentials.

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:
  • Python 3.9 or higher
  • A Composio account and API key
  • A Recallai connection authorized in Composio
  • An OpenAI API key for the CrewAI LLM
  • Basic familiarity with Python

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
  • Log in to the Composio dashboard.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.

Install dependencies

bash
pip install composio crewai crewai-tools[mcp] python-dotenv
What's happening:
  • composio connects your agent to Recallai via MCP
  • crewai provides Agent, Task, Crew, and LLM primitives
  • crewai-tools[mcp] includes MCP helpers
  • python-dotenv loads environment variables from .env

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
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 with Composio
  • USER_ID scopes the session to your account
  • OPENAI_API_KEY lets CrewAI use your chosen OpenAI model

Import dependencies

python
import os
from composio import Composio
from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
import dotenv

dotenv.load_dotenv()

COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set")
What's happening:
  • CrewAI classes define agents and tasks, and run the workflow
  • MCPServerHTTP connects the agent to an MCP endpoint
  • Composio will give you a short lived Recallai MCP URL

Create a Composio Tool Router session for Recallai

python
composio_client = Composio(api_key=COMPOSIO_API_KEY)
session = composio_client.create(user_id=COMPOSIO_USER_ID, toolkits=["recallai"])

url = session.mcp.url
What's happening:
  • You create a Recallai only session through Composio
  • Composio returns an MCP HTTP URL that exposes Recallai tools

Initialize the MCP Server

python
server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users search the internet effectively",
        backstory="You are a helpful assistant with access to search tools.",
        tools=tools,
        verbose=False,
        max_iter=10,
    )
What's Happening:
  • Server Configuration: The code sets up connection parameters including the MCP server URL, streamable HTTP transport, and Composio API key authentication.
  • MCP Adapter Bridge: MCPServerAdapter acts as a context manager that converts Composio MCP tools into a CrewAI-compatible format.
  • Agent Setup: Creates a CrewAI Agent with a defined role (Search Assistant), goal (help with internet searches), and access to the MCP tools.
  • Configuration Options: The agent includes settings like verbose=False for clean output and max_iter=10 to prevent infinite loops.
  • Dynamic Tool Usage: Once created, the agent automatically accesses all Composio Search tools and decides when to use them based on user queries.

Create a CLI Chatloop and define the Crew

python
print("Chat started! Type 'exit' or 'quit' to end.\n")

conversation_context = ""

while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ["exit", "quit", "bye"]:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    conversation_context += f"\nUser: {user_input}\n"
    print("\nAgent is thinking...\n")

    task = Task(
        description=(
            f"Conversation history:\n{conversation_context}\n\n"
            f"Current request: {user_input}"
        ),
        expected_output="A helpful response addressing the user's request",
        agent=agent,
    )

    crew = Crew(agents=[agent], tasks=[task], verbose=False)
    result = crew.kickoff()
    response = str(result)

    conversation_context += f"Agent: {response}\n"
    print(f"Agent: {response}\n")
What's Happening:
  • Interactive CLI Setup: The code creates an infinite loop that continuously prompts for user input and maintains the entire conversation history in a string variable.
  • Input Validation: Empty inputs are ignored to prevent processing blank messages and keep the conversation clean.
  • Context Building: Each user message is appended to the conversation context, which preserves the full dialogue history for better agent responses.
  • Dynamic Task Creation: For every user input, a new Task is created that includes both the full conversation history and the current request as context.
  • Crew Execution: A Crew is instantiated with the agent and task, then kicked off to process the request and generate a response.
  • Response Management: The agent's response is converted to a string, added to the conversation context, and displayed to the user, maintaining conversational continuity.

Complete Code

Here's the complete code to get you started with Recallai and CrewAI:

python
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter
from composio import Composio
from dotenv import load_dotenv
import os

load_dotenv()

GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not GOOGLE_API_KEY:
    raise ValueError("GOOGLE_API_KEY is not set in the environment.")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set in the environment.")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set in the environment.")

# Initialize Composio and create a session
composio = Composio(api_key=COMPOSIO_API_KEY)
session = composio.create(
    user_id=COMPOSIO_USER_ID,
    toolkits=["recallai"],
)
url = session.mcp.url

# Configure LLM
llm = LLM(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY"),
)

server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users with internet searches",
        backstory="You are an expert assistant with access to Composio Search tools.",
        tools=tools,
        llm=llm,
        verbose=False,
        max_iter=10,
    )

    print("Chat started! Type 'exit' or 'quit' to end.\n")

    conversation_context = ""

    while True:
        user_input = input("You: ").strip()

        if user_input.lower() in ["exit", "quit", "bye"]:
            print("\nGoodbye!")
            break

        if not user_input:
            continue

        conversation_context += f"\nUser: {user_input}\n"
        print("\nAgent is thinking...\n")

        task = Task(
            description=(
                f"Conversation history:\n{conversation_context}\n\n"
                f"Current request: {user_input}"
            ),
            expected_output="A helpful response addressing the user's request",
            agent=agent,
        )

        crew = Crew(agents=[agent], tasks=[task], verbose=False)
        result = crew.kickoff()
        response = str(result)

        conversation_context += f"Agent: {response}\n"
        print(f"Agent: {response}\n")

Conclusion

You now have a CrewAI agent connected to Recallai through Composio's Tool Router. The agent can perform Recallai operations through natural language commands.

Next steps:

  • Add role-specific instructions to customize agent behavior
  • Plug in more toolkits for multi-app workflows
  • Chain tasks for complex multi-step operations

How to build Recallai MCP Agent with another framework

FAQ

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

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

Can I use Tool Router MCP with CrewAI?

Yes, you can. CrewAI 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 Recallai tools.

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

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

Used by agents from

Context
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai
Context
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai
Context
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai

Never worry about agent reliability

We handle tool reliability, observability, and security so you never have to second-guess an agent action.