How to integrate Synthflow ai MCP with Pydantic AI

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Introduction

This guide walks you through connecting Synthflow ai to Pydantic AI 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 Pydantic AI 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:
  • How to set up your Composio API key and User ID
  • How to create a Composio Tool Router session for Synthflow ai
  • How to attach an MCP Server to a Pydantic AI agent
  • How to stream responses and maintain chat history
  • How to build a simple REPL-style chat interface to test your Synthflow ai workflows

What is Pydantic AI?

Pydantic AI is a Python framework for building AI agents with strong typing and validation. It leverages Pydantic's data validation capabilities to create robust, type-safe AI applications.

Key features include:

  • Type Safety: Built on Pydantic for automatic data validation
  • MCP Support: Native support for Model Context Protocol servers
  • Streaming: Built-in support for streaming responses
  • Async First: Designed for async/await patterns

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 with an active API key
  • Basic familiarity with Python and async programming

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 pydantic-ai python-dotenv

Install the required libraries.

What's happening:

  • composio connects your agent to external SaaS tools like Synthflow ai
  • pydantic-ai lets you create structured AI agents with tool support
  • python-dotenv loads your environment variables securely from a .env file

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

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your agent to Composio's API
  • USER_ID associates your session with your account for secure tool access
  • OPENAI_API_KEY to access OpenAI LLMs

Import dependencies

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()
What's happening:
  • We load environment variables and import required modules
  • Composio manages connections to Synthflow ai
  • MCPServerStreamableHTTP connects to the Synthflow ai MCP server endpoint
  • Agent from Pydantic AI lets you define and run the AI assistant

Create a Tool Router Session

python
async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Synthflow ai
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["synthflow_ai"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")
What's happening:
  • We're creating a Tool Router session that gives your agent access to Synthflow ai tools
  • The create method takes the user ID and specifies which toolkits should be available
  • The returned session.mcp.url is the MCP server URL that your agent will use

Initialize the Pydantic AI Agent

python
# Attach the MCP server to a Pydantic AI Agent
synthflow_ai_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[synthflow_ai_mcp],
    instructions=(
        "You are a Synthflow ai assistant. Use Synthflow ai tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the Synthflow ai endpoint
  • The agent uses GPT-5 to interpret user commands and perform Synthflow ai operations
  • The instructions field defines the agent's role and behavior

Build the chat interface

python
# Simple REPL with message history
history = []
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to help you with Synthflow ai.\n")

while True:
    user_input = input("You: ").strip()
    if user_input.lower() in {"exit", "quit", "bye"}:
        print("\nGoodbye!")
        break
    if not user_input:
        continue

    print("\nAgent is thinking...\n", flush=True)

    async with agent.run_stream(user_input, message_history=history) as stream_result:
        collected_text = ""
        async for chunk in stream_result.stream_output():
            text_piece = None
            if isinstance(chunk, str):
                text_piece = chunk
            elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                text_piece = chunk.delta
            elif hasattr(chunk, "text"):
                text_piece = chunk.text
            if text_piece:
                collected_text += text_piece
        result = stream_result

    print(f"Agent: {collected_text}\n")
    history = result.all_messages()
What's happening:
  • The agent reads input from the terminal and streams its response
  • Synthflow ai API calls happen automatically under the hood
  • The model keeps conversation history to maintain context across turns

Run the application

python
if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • The asyncio loop launches the agent and keeps it running until you exit

Complete Code

Here's the complete code to get you started with Synthflow ai and Pydantic AI:

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()

async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Synthflow ai
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["synthflow_ai"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")

    # Attach the MCP server to a Pydantic AI Agent
    synthflow_ai_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[synthflow_ai_mcp],
        instructions=(
            "You are a Synthflow ai assistant. Use Synthflow ai tools to help users "
            "with their requests. Ask clarifying questions when needed."
        ),
    )

    # Simple REPL with message history
    history = []
    print("Chat started! Type 'exit' or 'quit' to end.\n")
    print("Try asking the agent to help you with Synthflow ai.\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "bye"}:
            print("\nGoodbye!")
            break
        if not user_input:
            continue

        print("\nAgent is thinking...\n", flush=True)

        async with agent.run_stream(user_input, message_history=history) as stream_result:
            collected_text = ""
            async for chunk in stream_result.stream_output():
                text_piece = None
                if isinstance(chunk, str):
                    text_piece = chunk
                elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                    text_piece = chunk.delta
                elif hasattr(chunk, "text"):
                    text_piece = chunk.text
                if text_piece:
                    collected_text += text_piece
            result = stream_result

        print(f"Agent: {collected_text}\n")
        history = result.all_messages()

if __name__ == "__main__":
    asyncio.run(main())

Conclusion

You've built a Pydantic AI agent that can interact with Synthflow ai through Composio's Tool Router. With this setup, your agent can perform real Synthflow ai actions through natural language. You can extend this further by:
  • Adding other toolkits like Gmail, HubSpot, or Salesforce
  • Building a web-based chat interface around this agent
  • Using multiple MCP endpoints to enable cross-app workflows (for example, Gmail + Synthflow ai for workflow automation)
This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.

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 Pydantic AI?

Yes, you can. Pydantic 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 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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