How to integrate Insighto ai MCP with Pydantic AI

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Introduction

This guide walks you through connecting Insighto ai to Pydantic AI using the Composio tool router. By the end, you'll have a working Insighto ai agent that can send whatsapp message to all new leads, fetch conversation history for a specific contact, list all available chatbot intents today through natural language commands.

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

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

Also integrate Insighto 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 Insighto 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 Insighto 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 Insighto ai MCP server, and what's possible with it?

The Insighto 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 Insighto ai account. It provides structured and secure access to your conversational AI assets, so your agent can create new intents, manage contacts, analyze conversations, deploy widgets, and broadcast messages across channels on your behalf.

  • Intent creation and management: Easily add or review conversational intents to enhance your chatbots and voice agents, making them smarter and more responsive.
  • Bulk contact communication: Let your agent send messages to multiple contacts in bulk through WhatsApp or SMS, enabling efficient campaign blasts and customer updates.
  • Comprehensive contact and conversation insights: Retrieve full contact profiles, browse lists of contacts, and access detailed conversation metadata for analytics or personalized support.
  • Widget and provider deployment: Quickly create and configure new widgets and providers to extend your AI’s reach across new channels and platforms.
  • Datasource and metadata management: Fetch and inspect all data sources and custom contact fields, so your agent can sync, organize, or enrich customer data as needed.

Supported Tools & Triggers

Tools
Add Intent To AssistantTool to add an intent to an assistant in Insighto.
Create AgencyTool to create a new agency in Insighto.
Create Contact Custom FieldTool to create a new contact custom field in Insighto.
Create FormTool to create a new form in Insighto.
Create IntentTool to create a new intent in Insighto.
Create PromptTool to create a new prompt in Insighto.
Create ProviderCreates a new AI provider configuration (e.
Create TagTool to create a new tag in Insighto.
Create ToolfunctionTool to create a new toolfunction in Insighto.
Create WebhookTool to create a new outbound webhook in Insighto.
Create WidgetTool to create a new widget with specified attributes.
Delete Assistant By IDTool to delete an assistant by its ID.
Delete Bulk Forms By IDsTool to delete multiple forms by their IDs in a single operation.
Delete Contacts In BulkTool to delete multiple contacts in bulk.
Delete Form By IDTool to delete a form by its unique identifier.
Delete Linked Assistant DatasourceTool to delete (unlink) a datasource from a linked assistant in Insighto.
Delete Link Tag Entity By IDTool to delete a link_tag_entity by its ID.
Delete Prompt By IDTool to delete a prompt by its unique ID.
Delete Provider By IDTool to delete an AI provider configuration by its unique identifier.
Delete Tag By IDTool to delete a tag by its unique identifier.
Delete Tool By IDTool to delete a tool by its ID.
Delete Toolfunction By IDTool to delete a toolfunction by its ID.
Delete Twilio Auth By IDTool to delete a Twilio authentication configuration by its ID.
Delete UserWhatsApp By IDTool to delete a UserWhatsApp by its ID.
Delete Widget By IDTool to delete a widget by its unique ID.
Get Agency Billing PlanTool to retrieve details of a specific agency billing plan by ID.
Get Agency Branding By IDTool to retrieve branding configuration for a specific agency by agency ID.
Get Agent ListTool to fetch a paginated list of agents.
Get Assistant By IDTool to retrieve details of a specific assistant by assistant ID.
Get Captured Form By Form IDTool to retrieve captured form submissions by form ID.
Get Contact By IDTool to retrieve details of a specific contact by contact ID.
Get Datasource By IDTool to retrieve details of a specific datasource by datasource ID.
Get Intent By IDTool to retrieve details of a specific intent by its ID.
Get List Of ContactsTool to fetch a paginated list of contacts.
Get List Of ConversationsTool to fetch a list of conversations.
Get List Of DatasourcesRetrieves a paginated list of data sources from Insighto AI.
Get List Of Data Sources Linked To Assistant IdTool to retrieve a paginated list of data sources linked to a specific assistant.
Get List Of Widgets Linked To Assistant IdTool to fetch a paginated list of widgets linked to a specific assistant.
Get Pricing For UserTool to retrieve pricing information for Insighto.
Get Prompt By IDTool to retrieve details of a specific prompt by prompt ID.
Get Provider By IDTool to retrieve details of a specific provider by provider ID.
Get Speechtotext ListTool to fetch a paginated list of available speech-to-text voice configurations.
Get Widget By IDTool to retrieve details of a specific widget by widget ID.
List ChannelsTool to retrieve a paginated list of channels.
Read Campaign Contact ListTool to retrieve a paginated list of contacts associated with a specific campaign.
Read Contact Custom Field ListTool to retrieve a list of custom fields associated with contacts.
Read Contact Sync Log ListTool to retrieve a paginated list of contact sync logs.
Read Intents ListTool to retrieve a list of all intents.
Read Tag ListTool to retrieve a paginated list of tags.
Read Tool Function Invoke Log ListTool to retrieve a paginated list of tool function invoke logs.
Read Tool Toolfunction ListTool to retrieve a paginated list of tool functions for a specific tool.
Read Twilio Auth ListTool to retrieve a paginated list of Twilio authentications.
Retrieve Linked Tool And UserTool to retrieve linked tool and user information for a specific tool.
Retrieve List Of User Custom VoiceTool to retrieve a paginated list of user custom voices.
Retrieve User Monthly Usages AggregationTool to retrieve user monthly usages aggregation data.
Retrieve Webhook LogTool to retrieve webhook logs for a specific webhook.
Send Messages To ContactsTool to send messages to a list of contacts in bulk.
Update Link Tool UserTool to update a link tool user by its ID.
Update Tool By IDTool to update a tool by its ID.
Update Toolfunction By IDTool to update an existing toolfunction by its ID.
Update Twilio Auth By IDTool to update a Twilio authentication configuration by its ID.
Update User ProfileTool to update a user profile in Insighto.
Update UserWhatsApp By IDTool to update a UserWhatsApp configuration by its ID.
Update Webhook By IDTool to update an outbound webhook by its unique ID.
Upsert Contact By Email Or Phone NumberTool to upsert (create or update) a contact in Insighto.

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 Insighto 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 Insighto ai
  • MCPServerStreamableHTTP connects to the Insighto 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 Insighto ai
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["insighto_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 Insighto 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
insighto_ai_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[insighto_ai_mcp],
    instructions=(
        "You are a Insighto ai assistant. Use Insighto ai tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the Insighto ai endpoint
  • The agent uses GPT-5 to interpret user commands and perform Insighto 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 Insighto 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
  • Insighto 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 Insighto 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 Insighto ai
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["insighto_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
    insighto_ai_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[insighto_ai_mcp],
        instructions=(
            "You are a Insighto ai assistant. Use Insighto 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 Insighto 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 Insighto ai through Composio's Tool Router. With this setup, your agent can perform real Insighto 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 + Insighto 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.

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FAQ

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

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

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

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

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