How to integrate Nusii proposals MCP with Pydantic AI

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Introduction

This guide walks you through connecting Nusii proposals to Pydantic AI using the Composio tool router. By the end, you'll have a working Nusii proposals agent that can create a new proposal for acme corp, send a follow-up email for pending proposal, list all proposals sent in the last month through natural language commands.

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

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

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 Nusii proposals
  • 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 Nusii proposals 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 Nusii proposals MCP server, and what's possible with it?

The Nusii proposals MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Nusii proposals account. It provides structured and secure access so your agent can perform Nusii proposals operations on your behalf.

Supported Tools & Triggers

Tools
Archive ProposalTool to archive a specific proposal in Nusii.
Create ClientTool to create a new client in Nusii Proposals.
Create Line ItemTool to create a line item within a proposal section.
Create ProposalTool to create a new proposal in Nusii.
Create SectionTool to create a section for a proposal or template in Nusii Proposals.
Create Webhook EndpointTool to create a webhook endpoint to subscribe to Nusii events.
Delete a clientTool to delete a specific client from Nusii account.
Delete Line ItemTool to delete a line item from Nusii.
Delete a proposalTool to delete a proposal from the system.
Delete a sectionTool to delete a specific section from Nusii.
Delete Webhook EndpointTool to delete a specific webhook endpoint from the system.
Get Account MeTool to retrieve authenticated user's personal account information and settings.
Get ClientTool to retrieve a single client from Nusii using their unique identifier.
Get ProposalTool to retrieve a single proposal with complete details and sections.
Get SectionTool to retrieve a single section from a proposal or template in Nusii.
Get Webhook EndpointTool to retrieve a single webhook endpoint configuration.
List ClientsTool to retrieve all clients associated with the account.
List Line ItemsTool to retrieve all line items from Nusii Proposals with pagination support.
List Proposal ActivitiesTool to retrieve all proposal activities with optional filtering by proposal or client ID.
List ProposalsTool to retrieve all proposals from your Nusii account with pagination and filtering options.
List Section Line ItemsTool to retrieve all line items from a specific section.
List SectionsTool to retrieve all sections with optional filtering for proposals or templates.
List ThemesTool to retrieve all available themes for proposals in Nusii.
List UsersTool to retrieve all users in paginated format.
List Webhook EndpointsTool to retrieve all webhook endpoints configured for your Nusii account.
Update ClientTool to update an existing client's information in Nusii.
Update Line ItemTool to update an existing line item in Nusii proposals.
Update ProposalTool to update an existing proposal in Nusii.
Update SectionTool to update an existing section in a proposal or template.

What is the Composio tool router, and how does it fit here?

What is Tool Router?

Composio's Tool Router 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 Tool Router

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Tool Router works

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

FAQ

What are the differences in Tool Router MCP and Nusii proposals MCP?

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

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

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

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