How to integrate Synthflow ai MCP with CrewAI

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Introduction

This guide walks you through connecting Synthflow ai to CrewAI using the Composio tool router. By the end, you'll have a working Synthflow ai agent that can create a new ai assistant for customer support, list all current voice assistants in your account, fetch details for team 'sales outreach' through natural language commands.

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

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

Also integrate Synthflow ai with

TL;DR

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

The Synthflow ai MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Synthflow ai account. It provides structured and secure access to your voice automation tools, so your agent can perform actions like managing voice assistants, handling teams, retrieving phone numbers, and automating call center operations on your behalf.

  • AI assistant management: Create, list, update, or delete AI-powered voice assistants to tailor customer interactions and automate call flows as needed.
  • Team creation and configuration: Set up new teams, modify existing ones, or remove teams to optimize your call center's routing and operational structure.
  • Knowledge base integration: Retrieve and manage knowledge base details to ensure your assistants have accurate, up-to-date information for conversations.
  • Phone number administration: Fetch and organize phone numbers linked to your workspace, making it easy to assign or reassign numbers for inbound and outbound campaigns.
  • Comprehensive assistant and team insights: Access detailed metadata and configuration for both assistants and teams, streamlining oversight and decision-making for your AI-powered operations.

Supported Tools & Triggers

Tools
Add document to knowledge base sourceTool to add a document to a knowledge base source.
Attach Actions to AgentTool to attach one or more actions to an agent.
Attach contact to memory storeTool to attach a contact to a memory store.
Attach knowledge base to agentTool to attach a knowledge base to an agent.
Attach memory store to agentTool to attach a memory store to an agent.
Create ActionTool to create a new action in Synthflow AI.
Create AssistantTool to create a new assistant.
Create a contactTool to create a new contact in Synthflow AI.
Create knowledge baseTool to create a new knowledge base and return its ID.
Create memory storeTool to create a new memory store.
Create Phone BookTool to create a new phone book.
Create phone book entryTool to create a phone book entry.
Create Simulation CaseTool to create a new simulation case.
Create a simulation scenarioTool to create a new simulation scenario.
Create a new simulation suiteTool to create a new simulation suite attached to a specific agent.
Create a new teamTool to create a new team.
Delete an actionTool to delete an existing action.
Delete an assistantTool to delete an existing AI assistant.
Delete a chat sessionTool to delete a chat session.
Delete a contactTool to delete an existing contact.
Delete knowledge baseTool to delete an existing knowledge base.
Delete a knowledge base sourceTool to delete a source from a knowledge base.
Delete a memory storeTool to delete a memory store.
Delete a phone bookTool to delete an existing phone book.
Delete a phone book entryTool to delete a phone book entry.
Delete a simulation caseTool to delete a simulation case by ID.
Delete a simulation scenarioTool to delete an existing simulation scenario.
Delete a simulation suiteTool to delete a simulation suite by ID.
Delete a subaccountTool to delete an existing subaccount.
Delete a teamTool to delete an existing team.
Detach actions from assistantTool to detach one or more actions from an AI assistant.
Detach knowledge baseTool to detach a knowledge base from an AI assistant.
Detach contact from memory storeTool to detach a contact from a memory store.
Detach memory store from agentTool to detach a memory store from an agent.
Execute simulation suiteTool to execute all test cases in a simulation suite.
Export analytics dataTool to export analytics data for calls within a specified date range.
Get action metadataTool to retrieve metadata about a specific action by its ID.
Get AI assistant detailsTool to retrieve details of a specific AI assistant.
Get phone call detailsTool to retrieve the transcript and detailed metadata for a specific phone call.
Get contact detailsTool to retrieve details of a specific contact by its ID.
Get knowledge baseTool to retrieve details of a specific knowledge base by its ID.
Get memory storeTool to retrieve details of a specific memory store by its ID.
Get memory store contact dataTool to retrieve memory data for a specific contact in a memory store.
Get phone numbersTool to retrieve a list of phone numbers associated with a workspace.
Get simulation detailsTool to retrieve details of a specific simulation by ID.
Get Simulation CaseTool to retrieve a simulation case by ID.
Get simulation scenarioTool to retrieve a simulation scenario by ID.
Get simulation suite by IDTool to retrieve a simulation suite by ID.
Get subaccount detailsTool to retrieve detailed metadata about a specific subaccount by ID.
Get team detailsTool to retrieve details of a specific team by its ID.
Initialize ActionTool to initialize a custom action with specified variables.
List actionsTool to list all actions in the workspace.
List AI assistantsTool to list all AI assistants associated with the account.
List call historyTool to retrieve call history (call logs) with filtering to check outcomes/statuses after placing calls.
List chatsTool to retrieve a list of chats, optionally filtered by agent ID.
List contactsTool to retrieve a list of contacts with optional search filtering.
List memory storesTool to list memory stores with optional filtering by title.
List Phone BooksTool to list all phone books in your workspace.
List Simulation CasesTool to list simulation cases with pagination and optional filtering by name or type.
List simulation cases by agentTool to list all simulation cases created for a specific agent.
List simulationsTool to list simulations with pagination and optional filters.
List simulation scenariosTool to list simulation scenarios with pagination and optional filtering.
List simulation sessionsTool to list simulation sessions with pagination and optional filters.
List simulation suitesTool to list simulation suites with pagination and optional filtering.
List subaccountsTool to list all subaccounts associated with the authenticated account.
List teamsTool to list assistant teams.
List voicesTool to list all text-to-speech voices in a workspace.
List webhook logsTool to retrieve paginated webhook logs with filtering and search capability.
Make a voice callTool to initiate a real-time voice call via the AI agent.
Start SimulationTool to start a new simulation using a simulation case.
Update ActionTool to update an existing action in Synthflow AI.
Update AssistantTool to update an existing assistant’s settings.
Update a contactTool to update an existing contact in Synthflow AI.
Update knowledge baseTool to update an existing knowledge base's name or usage conditions.
Update memory storeTool to update an existing memory store's title and description.
Update Simulation CaseTool to update an existing simulation case.
Update a simulation scenarioTool to update an existing simulation scenario.
Update an existing simulation suiteTool to update an existing simulation suite.
Update an existing teamTool to update an existing team.

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 Synthflow ai 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 Synthflow ai 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 Synthflow ai MCP URL

Create a Composio Tool Router session for Synthflow ai

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

url = session.mcp.url
What's happening:
  • You create a Synthflow ai only session through Composio
  • Composio returns an MCP HTTP URL that exposes Synthflow ai 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 Synthflow ai 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=["synthflow_ai"],
)
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 Synthflow ai through Composio's Tool Router. The agent can perform Synthflow ai 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 Synthflow ai MCP Agent with another framework

FAQ

What are the differences in Tool Router MCP and Synthflow ai MCP?

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

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

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

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