How to integrate Fireberry MCP with Autogen

This guide walks you through connecting Fireberry to AutoGen 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 AutoGen 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.

Get started for freeGet a demo
Fireberry logoFireberry
Api Key

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 AutoGen 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 AutoGen 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

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAI

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Install the required dependencies for Autogen and Composio
  • Initialize Composio and create a Tool Router session for Fireberry
  • Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
  • Configure an Autogen AssistantAgent that can call Fireberry tools
  • Run a live chat loop where you ask the agent to perform Fireberry operations

What is AutoGen?

Autogen is a framework for building multi-agent conversational AI systems from Microsoft. It enables you to create agents that can collaborate, use tools, and maintain complex workflows.

Key features include:

  • Multi-Agent Systems: Build collaborative agent workflows
  • MCP Workbench: Native support for Model Context Protocol tools
  • Streaming HTTP: Connect to external services through streamable HTTP
  • AssistantAgent: Pre-built agent class for tool-using assistants

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 step08 STEPS
1

Prerequisites

You will need:

  • A Composio API key
  • An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
  • A Fireberry account you can connect to Composio
  • Some basic familiarity with Autogen and Python async
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 python-dotenv
pip install autogen-agentchat autogen-ext-openai autogen-ext-tools

Install Composio, Autogen extensions, and dotenv.

What's happening:

  • composio connects your agent to Fireberry via MCP
  • autogen-agentchat provides the AssistantAgent class
  • autogen-ext-openai provides the OpenAI model client
  • autogen-ext-tools provides MCP workbench support

4

Set up environment variables

bash
COMPOSIO_API_KEY=your-composio-api-key
OPENAI_API_KEY=your-openai-api-key
USER_ID=your-user-identifier@example.com

Create a .env file in your project folder.

What's happening:

  • COMPOSIO_API_KEY is required to talk to Composio
  • OPENAI_API_KEY is used by Autogen's OpenAI client
  • USER_ID is how Composio identifies which user's Fireberry connections to use
5

Import dependencies and create Tool Router session

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Fireberry session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["fireberry"]
    )
    url = session.mcp.url
What's happening:
  • load_dotenv() reads your .env file
  • Composio(api_key=...) initializes the SDK
  • create(...) creates a Tool Router session that exposes Fireberry tools
  • session.mcp.url is the MCP endpoint that Autogen will connect to
6

Configure MCP parameters for Autogen

python
# Configure MCP server parameters for Streamable HTTP
server_params = StreamableHttpServerParams(
    url=url,
    timeout=30.0,
    sse_read_timeout=300.0,
    terminate_on_close=True,
    headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
)

Autogen expects parameters describing how to talk to the MCP server. That is what StreamableHttpServerParams is for.

What's happening:

  • url points to the Tool Router MCP endpoint from Composio
  • timeout is the HTTP timeout for requests
  • sse_read_timeout controls how long to wait when streaming responses
  • terminate_on_close=True cleans up the MCP server process when the workbench is closed
7

Create the model client and agent

python
# Create model client
model_client = OpenAIChatCompletionClient(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY")
)

# Use McpWorkbench as context manager
async with McpWorkbench(server_params) as workbench:
    # Create Fireberry assistant agent with MCP tools
    agent = AssistantAgent(
        name="fireberry_assistant",
        description="An AI assistant that helps with Fireberry operations.",
        model_client=model_client,
        workbench=workbench,
        model_client_stream=True,
        max_tool_iterations=10
    )

What's happening:

  • OpenAIChatCompletionClient wraps the OpenAI model for Autogen
  • McpWorkbench connects the agent to the MCP tools
  • AssistantAgent is configured with the Fireberry tools from the workbench
8

Run the interactive chat loop

python
print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Fireberry related question or task to the agent.\n")

# Conversation loop
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")

    # Run the agent with streaming
    try:
        response_text = ""
        async for message in agent.run_stream(task=user_input):
            if hasattr(message, "content") and message.content:
                response_text = message.content

        # Print the final response
        if response_text:
            print(f"Agent: {response_text}\n")
        else:
            print("Agent: I encountered an issue processing your request.\n")

    except Exception as e:
        print(f"Agent: Sorry, I encountered an error: {str(e)}\n")
What's happening:
  • The script prompts you in a loop with You:
  • Autogen passes your input to the model, which decides which Fireberry tools to call via MCP
  • agent.run_stream(...) yields streaming messages as the agent thinks and calls tools
  • Typing exit, quit, or bye ends the loop

Complete Code

Here's the complete code to get you started with Fireberry and AutoGen:

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Fireberry session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["fireberry"]
    )
    url = session.mcp.url

    # Configure MCP server parameters for Streamable HTTP
    server_params = StreamableHttpServerParams(
        url=url,
        timeout=30.0,
        sse_read_timeout=300.0,
        terminate_on_close=True,
        headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
    )

    # Create model client
    model_client = OpenAIChatCompletionClient(
        model="gpt-5",
        api_key=os.getenv("OPENAI_API_KEY")
    )

    # Use McpWorkbench as context manager
    async with McpWorkbench(server_params) as workbench:
        # Create Fireberry assistant agent with MCP tools
        agent = AssistantAgent(
            name="fireberry_assistant",
            description="An AI assistant that helps with Fireberry operations.",
            model_client=model_client,
            workbench=workbench,
            model_client_stream=True,
            max_tool_iterations=10
        )

        print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
        print("Ask any Fireberry related question or task to the agent.\n")

        # Conversation loop
        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")

            # Run the agent with streaming
            try:
                response_text = ""
                async for message in agent.run_stream(task=user_input):
                    if hasattr(message, 'content') and message.content:
                        response_text = message.content

                # Print the final response
                if response_text:
                    print(f"Agent: {response_text}\n")
                else:
                    print("Agent: I encountered an issue processing your request.\n")

            except Exception as e:
                print(f"Agent: Sorry, I encountered an error: {str(e)}\n")

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

Conclusion

You now have an Autogen assistant wired into Fireberry through Composio's Tool Router and MCP. From here you can:
  • Add more toolkits to the toolkits list, for example notion or hubspot
  • Refine the agent description to point it at specific workflows
  • Wrap this script behind a UI, Slack bot, or internal tool
Once the pattern is clear for Fireberry, you can reuse the same structure for other MCP-enabled apps with minimal code changes.
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. Autogen 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.

Start with Fireberry.It takes 30 seconds.

Managed auth, hosted MCP servers, and every Fireberry tool your agent needs.Free to start.

Start building
Customer stories

Teams ship real agents on Composio

GET STARTED FOR FREEBOOK A DEMO
agent.aiZoomLettaGleanHubSpotAWSWabi

Karan skipped his own birthday party to fix our critical issue. It was 10pm and he diverted his Waymo to help us instead. This really sets the bar — it shows the commitment you need when users rely on your software.

Harsha Gaddipati
Harsha Gaddipati
Co-founder, Slashy

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.

Abhi Arya
Abhi Arya
Co-founder, Opennote

We chose Composio over Pipedream because it delivered depth where it mattered — niche tools and tricky edge cases other platforms simply ignored. That gave us confidence to scale without compromising.

Nirman Dave
Nirman Dave
CEO, Zams

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.

Ryan Yu
Ryan Yu
Founder, Extra Thursday

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.

Tomisin Jenrola
Tomisin Jenrola
Founder & CEO, SwarmZero

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.

Jerome Leclanche
Jerome Leclanche
Co-Founder, Ingram Technologies