How to integrate Fireberry MCP with Pydantic AI

This guide walks you through connecting Fireberry to Pydantic AI using the Composio tool router. By the end, you'll have a working Fireberry agent that can add new lead to contacts table, list all open deals in pipeline, fetch picklist options for deal stage through natural language commands. This guide will help you understand how to give your Pydantic AI agent real control over a Fireberry account through Composio's Fireberry MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Fireberry is a CRM platform that streamlines customer and sales management. It helps businesses organize contacts, automate sales, and integrate with other business tools.

123 Tools

Introduction

This guide walks you through connecting Fireberry to Pydantic AI using the Composio tool router. By the end, you'll have a working Fireberry agent that can add new lead to contacts table, list all open deals in pipeline, fetch picklist options for deal stage through natural language commands.

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

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

Also integrate Fireberry with

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

The Fireberry MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Fireberry CRM account. It provides structured and secure access to your CRM data, so your agent can perform actions like creating records, querying customer information, and managing picklists on your behalf.

  • Automated record creation: Let your agent swiftly add new entries to any Fireberry table, such as contacts, leads, or deals, using structured data you provide.
  • Smart CRM data retrieval: Ask your agent to query records with powerful filtering, sorting, and pagination—perfect for finding the exact customer or deal you need.
  • Picklist value management: Effortlessly fetch all available options for any picklist (dropdown) field, making data entry and workflow automation simpler and error-free.
  • Custom module support: Enable your agent to work with any Fireberry module, so you can handle specialized business processes or custom workflows.

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 step09 STEPS
1

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
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 pydantic-ai python-dotenv

Install the required libraries.

What's happening:

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

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
5

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 Fireberry
  • MCPServerStreamableHTTP connects to the Fireberry MCP server endpoint
  • Agent from Pydantic AI lets you define and run the AI assistant
6

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 Fireberry
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["fireberry"],
    )
    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 Fireberry 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
7

Initialize the Pydantic AI Agent

python
# Attach the MCP server to a Pydantic AI Agent
fireberry_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[fireberry_mcp],
    instructions=(
        "You are a Fireberry assistant. Use Fireberry tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the Fireberry endpoint
  • The agent uses GPT-5 to interpret user commands and perform Fireberry operations
  • The instructions field defines the agent's role and behavior
8

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 Fireberry.\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
  • Fireberry API calls happen automatically under the hood
  • The model keeps conversation history to maintain context across turns
9

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 Fireberry 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 Fireberry
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["fireberry"],
    )
    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
    fireberry_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[fireberry_mcp],
        instructions=(
            "You are a Fireberry assistant. Use Fireberry 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 Fireberry.\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 Fireberry through Composio's Tool Router. With this setup, your agent can perform real Fireberry 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 + Fireberry for workflow automation)
This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.
TOOLS

Supported Tools

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

Create a Competitor

Tool to create a new competitor in Fireberry.

Create a Fireberry contact

Tool to create a new contact in Fireberry CRM.

Create an Activity Log

Create a new Activity Log record in Fireberry.

Create a date field

Tool to create a new date field in a Fireberry object/table.

Create a Fireberry lookup field

Tool to create a lookup field in Fireberry CRM.

Create a new Fireberry account

Tool to create a new account in Fireberry CRM.

Create an Article

Tool to create a new article in Fireberry.

Create a Fireberry asset

Creates a new asset (account product) in Fireberry.

Create an Opportunity

Tool to create a new opportunity in Fireberry CRM.

Create an Order Item

Tool to create a new order item in Fireberry CRM.

Create a note

Create a new note record in Fireberry.

Create a phone call

Creates a new phone call record in Fireberry's call log.

Create a Fireberry product

Tool to create a new product in Fireberry.

Create a Project

Tool to create a new project in Fireberry CRM.

Create a Task

Tool to create a new task in Fireberry CRM.

Create a Ticket

Tool to create a new ticket (case) in Fireberry CRM.

Create a URL field

Tool to create a new URL field in a Fireberry object/table.

Create a Campaign

Tool to create a new campaign in Fireberry.

Create a CRM Order

Tool to create a new CRM Order in Fireberry.

Upload file to Fireberry record

Tool to upload a file to a specific record in Fireberry.

Create a Fireberry meeting

Tool to create a new meeting (activity) in Fireberry.

Create a new Fireberry record

Creates a new record in a specified Fireberry table/module.

Delete an Account

Tool to delete an account from Fireberry using its GUID.

Delete a Competitor

Tool to delete a competitor in Fireberry by its GUID.

Delete a contract

Tool to delete a contract in Fireberry by its GUID.

Delete an Activity Log

Delete an activity log by its GUID.

Delete a custom field

Tool to delete a custom field from a Fireberry object/table.

Delete an Article

Tool to delete an article from Fireberry by its GUID.

Delete a Fireberry asset

Delete an asset from Fireberry by its unique identifier.

Delete an Opportunity

Tool to delete an opportunity in Fireberry by its GUID.

Delete an Order Item

Tool to delete an order item in Fireberry by its GUID.

Delete a Note

Tool to delete a note from Fireberry using its GUID.

Delete a Phone Call

Tool to delete a phone call record from Fireberry using its GUID.

Delete a project

Tool to delete a project from Fireberry using its GUID.

Delete a task

Tool to delete a task in Fireberry by its GUID.

Delete a ticket

Tool to delete a ticket (case) from Fireberry using its GUID.

Delete a Business Unit

Tool to delete a Business Unit in Fireberry using its GUID.

Delete a Fireberry campaign

Tool to delete a campaign from Fireberry.

Delete a Contact

Tool to delete a contact from Fireberry using its GUID.

Delete a CRM User

Tool to delete a CRM user from Fireberry using its GUID.

Delete a Meeting

Tool to delete a meeting activity from Fireberry by its GUID.

Delete a product

Tool to delete a product in Fireberry by its GUID.

Get an Account

Tool to retrieve a specific account record by its GUID.

Get a CRM Order

Tool to retrieve a specific CRM Order from Fireberry by its GUID.

Get All Accounts

Tool to retrieve all accounts from Fireberry CRM with pagination support.

Get All Activity Logs (v2)

Tool to retrieve all activity logs from Fireberry using v2 API endpoint with pagination support.

Get all articles from Fireberry

Tool to retrieve all articles from Fireberry with pagination support.

Get All Assets

Tool to retrieve all assets (account products) from Fireberry with pagination support.

Get All Business Units (v2)

Tool to retrieve all business units from Fireberry using v2 API endpoint with pagination support.

Get All Campaigns

Tool to retrieve all campaigns from Fireberry with pagination support.

Get All Competitors (v2)

Tool to retrieve all competitors from Fireberry with pagination support.

Get All Contacts

Tool to retrieve all contacts from Fireberry with pagination support.

Get All Contracts

Tool to retrieve all contracts from Fireberry with pagination support.

Get All Custom Object Records

Tool to retrieve all records from a specified custom object in Fireberry with pagination support.

Get All Meetings

Tool to retrieve all meetings (activities) from Fireberry CRM with pagination support.

Get All Notes (Detailed)

Tool to retrieve all notes from Fireberry with detailed field schema and pagination support.

Get All Objects

Tool to retrieve all object type metadata from Fireberry.

Get All Order Items

Tool to retrieve all order items from Fireberry with pagination support.

Get All Orders

Tool to retrieve all orders from Fireberry with pagination support.

Get All Phone Calls

Tool to retrieve all phone call records from Fireberry with pagination support.

Get All Projects (v2)

Tool to retrieve all projects from Fireberry with pagination support.

Get All Tasks

Tool to retrieve all tasks from Fireberry with pagination support.

Get All Tickets

Tool to retrieve all ticket records (cases) from Fireberry with pagination support.

Get All Users

Tool to retrieve all CRM users from Fireberry with pagination support.

Get a Meeting

Tool to retrieve a specific meeting/activity record by its unique identifier (GUID).

Get an Activity Log

Tool to retrieve a specific activity log record from Fireberry by its GUID.

Get an Article

Tool to retrieve a specific article from Fireberry by its GUID.

Get an Asset

Tool to retrieve a specific asset record by its GUID.

Get an Object

Tool to retrieve metadata for a specific object by its ID.

Get an Object's Fields

Tool to retrieve metadata about fields for a specific object type in Fireberry.

Get an Opportunity

Tool to retrieve a specific opportunity record by its GUID.

Get an Order Item

Tool to retrieve a specific order item record by its GUID.

Get a Note

Tool to retrieve a specific note record by its GUID.

Get a phone call record

Tool to retrieve a specific phone call record from Fireberry by its GUID.

Get a Product

Tool to retrieve a specific product record by its GUID.

Get a Project

Tool to retrieve a specific project from Fireberry by its GUID.

Get a Task

Tool to retrieve a specific task record by its GUID.

Get a Ticket

Tool to retrieve a specific ticket (case) record by its GUID.

Get Campaign by ID

Tool to retrieve a single campaign by its GUID.

Get a Competitor

Tool to retrieve a specific competitor record by its GUID.

Get a Contact

Tool to retrieve a specific contact record by its GUID.

Get Custom Object Record

Tool to retrieve a specific custom object record by its GUID and object code.

Get Field Details

Tool to retrieve detailed metadata for a specific field in a Fireberry object/table.

Get Object Field Values

Tool to retrieve picklist field values from the metadata endpoint.

Get Items for an Order

Tool to retrieve all items for a specific order from Fireberry.

Get Picklist Field Values

Tool to retrieve picklist field values from Fireberry metadata API.

Get Picklist Values

Tool to retrieve all possible picklist (dropdown) values for a specific field by querying records and extracting unique values.

Get Related Records

Tool to retrieve related records for a specific object in Fireberry.

Get Fireberry Task by ID

Tool to retrieve a single task record by its unique ID (GUID).

Get a Fireberry user by ID

Tool to retrieve a single user by their unique ID from Fireberry.

List All Opportunities

Tool to retrieve all opportunities from Fireberry CRM with pagination support.

List All Products

Tool to retrieve all products from Fireberry CRM with pagination support.

Fireberry: Query Records

Query and retrieve records from a Fireberry module with optional filtering, sorting, and pagination.

Query Fireberry records with filters

Query records in any Fireberry object with advanced filtering, sorting, and pagination.

Update a Business Unit

Tool to update an existing business unit in Fireberry.

Update Fireberry Account

Updates an existing account record in Fireberry with new field values.

Update a Fireberry Competitor

Updates an existing competitor record in Fireberry by GUID.

Update a Fireberry contact

Tool to update an existing contact in Fireberry CRM.

Update a Contract

Tool to update an existing contract in Fireberry.

Update an Activity Log

Update an existing Activity Log record in Fireberry.

Update a Date Field

Tool to update a date field configuration in Fireberry.

Update a Date & Time Field

Tool to update a Date & Time field's properties in Fireberry.

Update a Formula Field

Tool to update a formula field in Fireberry CRM.

Update an HTML Field

Tool to update an HTML field configuration in Fireberry.

Update a Fireberry Meeting

Tool to update an existing meeting (activity) in Fireberry.

Update a Fireberry article

Updates an existing article in Fireberry.

Update an Asset

Update an existing asset (accountproduct) in Fireberry.

Update an Email Address Field

Tool to update the configuration of an email address field in Fireberry.

Update an Opportunity

Tool to update an existing opportunity in Fireberry CRM.

Update an Order Item

Tool to update an existing order item in Fireberry.

Update a Number Field

Tool to update a number field configuration in Fireberry.

Update a Phone Number Field

Tool to update a phone number field configuration in Fireberry.

Update a Product

Tool to update an existing product in Fireberry.

Update a Project

Tool to update an existing project in Fireberry CRM.

Update a Text Area Field

Tool to update a Text Area field's properties in Fireberry.

Update a Text Field

Tool to update a text field configuration in Fireberry.

Update a Ticket

Tool to update an existing ticket (case) in Fireberry.

Update a URL Field

Tool to update a URL field configuration in Fireberry.

Update a User

Tool to update an existing user in Fireberry CRM.

Update a Fireberry Campaign

Tool to update an existing campaign in Fireberry by its GUID.

Update a CRM Order

Tool to update an existing CRM order in Fireberry.

Update a phone call record

Tool to update an existing phone call record in Fireberry.

Update a Task (V2)

Tool to update an existing task using Fireberry v2 API.

FRAMEWORKS

How to build Fireberry MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Fireberry MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Fireberry MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Fireberry MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Fireberry MCP with Claude Cowork

Codex logo

Codex

Use Fireberry MCP with Codex

OpenClaw logo

OpenClaw

Use Fireberry MCP with OpenClaw

Hermes logo

Hermes

Use Fireberry MCP with Hermes

CLI logo

CLI

Use Fireberry MCP with CLI

Google ADK logo

Google ADK

Use Fireberry MCP with Google ADK

LangChain logo

LangChain

Use Fireberry MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Fireberry MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Fireberry MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Fireberry MCP with LlamaIndex

CrewAI logo

CrewAI

Use Fireberry MCP with CrewAI

FAQ

Frequently asked questions

With a standalone Fireberry MCP server, the agents and LLMs can only access a fixed set of Fireberry tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Fireberry and many other apps based on the task at hand, all through a single MCP endpoint.

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 Fireberry tools.

Yes, absolutely. You can configure which Fireberry 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.

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 Fireberry data and credentials are handled as safely as possible.

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A lot of students tell us that the moment their connected tools start talking to each other inside Opennote feels almost magical. The agent just knows them, and it's immensely helped keep new users on the platform.

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As a solo builder, shipping fast is life or death. The only way I can outcompete incumbents is by outmanoeuvring them. Getting bogged down managing agent auth would have been a death sentence.

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Before Composio, adding tool integrations was slow and resource-intensive. Each one could take weeks of engineering time, and maintaining them meant constantly keeping up with API changes.

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With hands-on help from their founder, we integrated Gmail and Google Drive in just 30 minutes. This level of personal support and commitment is exactly what startups should strive for.

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