SIGN UPLOG IN
X (Twitter)LinkedInGitHubDiscordYouTube

How to integrate Callingly MCP with CrewAI

Connect CrewAI to Callingly MCP. Activate a client account for onboarding, create an outbound call to new lead, and more using natural language, with authentication handled for you.

Get started for freeGet a demo
Callingly logoCallingly
Api Key

Callingly is a lead response management platform that automates immediate call and text follow-ups with new leads. It helps sales teams boost response speed and close more deals by connecting seamlessly with CRMs and lead sources.

29 Tools

Introduction

This guide walks you through connecting Callingly to CrewAI using the Composio tool router. By the end, you'll have a working Callingly agent that can place outbound calls, manage leads, list calls, organize agents and teams, and update agent schedules through natural language commands.

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

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

For exact tool slugs and parameter tables, see the tool catalog in the Composio docs.

Also integrate Callingly with

Claude CodeClaude CoworkOpenAI Agents SDKClaude Agent SDKGrok BotCodexOpenClawHermesAtomic AgentGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexPydantic AIAutoGen

TL;DR

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

The Callingly MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Callingly account. It provides structured and secure access to your Callingly environment, so your agent can automate lead follow-ups, manage agents and clients, trigger outbound calls, and keep your sales workflows moving without manual intervention.

  • Automated outbound call creation: Instantly generate outbound call records so your team can respond to new leads within seconds without lifting a finger.
  • Agent and team management: Let your agent create, delete, or update agents and teams as your sales organization changes and grows.
  • Client onboarding and offboarding: Seamlessly add, activate, deactivate, or remove client accounts as your business requires—no more manual data entry.
  • Real-time webhook setup: Set up and delete webhooks to receive instant notifications for specific call or lead events, keeping your CRM and other tools in sync.
  • Availability and scheduling insights: Retrieve agent schedules to optimize call assignments and guarantee leads get connected when agents are actually available.

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 step08 STEPS
1

Prerequisites

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account and API key
  • A Callingly connection authorized in Composio
  • An OpenAI API key for the CrewAI LLM
  • Basic familiarity with Python
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
  • 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.
3

Install dependencies

bash
pip install composio crewai crewai-tools[mcp] python-dotenv
What's happening:
  • composio connects your agent to Callingly via MCP
  • crewai provides Agent, Task, Crew, and LLM primitives
  • crewai-tools[mcp] includes MCP helpers
  • python-dotenv loads environment variables from .env
4

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
5

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 Callingly MCP URL
6

Create a Composio Tool Router session for Callingly

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

url = session.mcp.url
What's happening:
  • You create a Callingly only session through Composio
  • Composio returns an MCP HTTP URL that exposes Callingly tools
7

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.
8

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 Callingly 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=["callingly"],
)
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 Callingly through Composio's Tool Router. The agent can perform Callingly 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
TOOLS

Supported Tools

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

Activate/Deactivate Client Account

Tool to activate or deactivate a client account.

Create Agent

Tool to create a new agent.

Create Outbound Call

Creates a new outbound call record and initiates a real outbound call, which incurs cost — ensure explicit user authorization and compliance with applicable consent and telemarketing regulations before use.

Create Client

Creates a new client account in Callingly.

Create Team

Tool to create a new team.

Create Webhook

Tool to create a new webhook for call or lead events.

Delete Agent

Permanently delete an agent from a Callingly account.

Delete Client

Tool to delete a client.

Delete Lead

Deletes a lead by ID.

Delete Webhook

Tool to delete a webhook.

Get Agent Schedule

Tool to retrieve the availability schedule for a specific agent.

Get Call

Retrieves detailed information about a specific call by its unique ID.

Get Lead

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

Get Team

Retrieve a Callingly team by ID to inspect its configuration, including call distribution, recording, and retry settings.

Get Webhook

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

List Calls

Tool to list calls.

List Clients

List clients associated with the Callingly account, including their identifying and billing details.

List Leads

Tool to list leads based on provided filters like date range or phone number.

List Teams

Tool to list teams.

List Team Users

Retrieve all agents assigned to a specific team in Callingly.

List Users

Tool to retrieve a list of agents.

List Webhooks

Tool to list configured webhooks.

Remove Team Agent

Tool to remove a specific agent from a team.

Update Agent

Tool to update an existing agent's details.

Update Lead

Tool to update an existing lead's information.

Update Agent Schedule

Tool to update an agent's availability schedule.

Update Team Agent Settings

Update a specific team agent's priority and call capacity.

Update Team Users

Updates the list of agents assigned to a team.

Update Webhook

Updates an existing webhook's configuration by ID.

FRAMEWORKS

How to build Callingly MCP Agent with another framework

Claude Code logo

Claude Code

Use Callingly MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Callingly MCP with Claude Cowork

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Callingly MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Callingly MCP with Claude Agent SDK

Grok Bot logo

Grok Bot

Use Callingly MCP with Grok Bot

Codex logo

Codex

Use Callingly MCP with Codex

OpenClaw logo

OpenClaw

Use Callingly MCP with OpenClaw

Hermes logo

Hermes

Use Callingly MCP with Hermes

Atomic Agent logo

Atomic Agent

Use Callingly MCP with Atomic Agent

Google ADK logo

Google ADK

Use Callingly MCP with Google ADK

LangChain logo

LangChain

Use Callingly MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Callingly MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Callingly MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Callingly MCP with LlamaIndex

Pydantic AI logo

Pydantic AI

Use Callingly MCP with Pydantic AI

AutoGen logo

AutoGen

Use Callingly MCP with AutoGen

FAQ

Frequently asked questions

Start with Callingly.It takes 30 seconds.

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

Start building