How to integrate Fidel api MCP with CrewAI

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Introduction

This guide walks you through connecting Fidel api to CrewAI using the Composio tool router. By the end, you'll have a working Fidel api agent that can register a new loyalty program for our stores, create a webhook for real-time offer updates, fetch details of a specific payment brand, delete an expired offer from our platform through natural language commands.

This guide will help you understand how to give your CrewAI agent real control over a Fidel api account through Composio's Fidel api 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:
  • Get a Composio API key and configure your Fidel api connection
  • Set up CrewAI with an MCP enabled agent
  • Create a Tool Router session or standalone MCP server for Fidel api
  • Build a conversational loop where your agent can execute Fidel api operations

What is CrewAI?

CrewAI is a powerful framework for building multi-agent AI systems. It provides primitives for defining agents with specific roles, creating tasks, and orchestrating workflows through crews.

Key features include:

  • Agent Roles: Define specialized agents with specific goals and backstories
  • Task Management: Create tasks with clear descriptions and expected outputs
  • Crew Orchestration: Combine agents and tasks into collaborative workflows
  • MCP Integration: Connect to external tools through Model Context Protocol

What is the Fidel api MCP server, and what's possible with it?

The Fidel api MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Fidel api account. It provides structured and secure access to your Fidel API tools, so your agent can perform actions like creating brands, managing programs, retrieving offers, handling webhooks, and more on your behalf.

  • Brand and program creation: Easily instruct your agent to register new brands or set up loyalty programs for your business, streamlining onboarding and expansion.
  • Real-time webhook management: Let your agent create or delete webhooks so you can receive instant notifications for important program events without manual setup.
  • Detailed entity retrieval: Have your agent fetch comprehensive details about brands, programs, offers, or webhooks whenever you need insights or verification.
  • Offer and webhook deletion: Direct your agent to remove outdated offers or webhooks, keeping your Fidel API environment clean and up-to-date.
  • End-to-end automation for payment integrations: Allow your agent to manage the full lifecycle of brands, programs, and event hooks, helping you build seamless payment-linked experiences with minimal effort.

Supported Tools & Triggers

Tools
Create BrandTool to create a new brand on fidel.
Create ProgramTool to create a new program.
Create Program WebhookTool to register a new webhook for program-related events.
Delete OfferTool to delete a specified offer by its id.
Delete Program WebhookTool to delete a specified webhook for a program.
Delete WebhookTool to delete a specified webhook.
Get BrandTool to retrieve information about a specific brand.
Get OfferTool to fetch details of a specific offer.
Get ProgramTool to retrieve details of a specific program.
Get WebhookTool to retrieve details of a specific webhook.
List BrandsTool to list all brands.
List CardsTool to list all cards for a specific program.
List LocationsTool to list all locations for a program.
List OffersTool to list all offers.
List ProgramsTool to list fidel programs.
List Program WebhooksTool to list all registered webhooks for a specific program.
List TransactionsTool to list transactions.
Update ProgramTool to update a program's name, icon, metadata, or status.

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 and API key
  • A Fidel api connection authorized in Composio
  • An OpenAI API key for the CrewAI LLM
  • Basic familiarity with Python

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 crewai crewai-tools python-dotenv
What's happening:
  • composio connects your agent to Fidel api via MCP
  • crewai provides Agent, Task, Crew, and LLM primitives
  • crewai-tools includes MCP helpers
  • python-dotenv loads environment variables from .env

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_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates with Composio
  • USER_ID scopes the session to your account
  • OPENAI_API_KEY lets CrewAI use your chosen OpenAI model

Import dependencies

python
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter  # optional import if you plan to adapt tools
from composio import Composio
from dotenv import load_dotenv
import os
from crewai.mcp import MCPServerHTTP

load_dotenv()
What's happening:
  • CrewAI classes define agents and tasks, and run the workflow
  • MCPServerHTTP connects the agent to an MCP endpoint
  • Composio will give you a short lived Fidel api MCP URL

Create a Composio Tool Router session for Fidel api

python
composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
session = composio.create(
    user_id=os.getenv("USER_ID"),
    toolkits=["fidel_api"],
)
url = session.mcp.url
What's happening:
  • You create a Fidel api only session through Composio
  • Composio returns an MCP HTTP URL that exposes Fidel api tools

Configure the LLM

python
llm = LLM(
    model="gpt-5-mini",
    api_key=os.getenv("OPENAI_API_KEY"),
)
What's happening:
  • CrewAI will call this LLM for planning and responses
  • You can swap in a different model if needed

Attach the MCP server and create the agent

python
toolkit_agent = Agent(
    role="Fidel api Assistant",
    goal="Help users interact with Fidel api through natural language commands",
    backstory=(
        "You are an expert assistant with access to Fidel api tools. "
        "You can perform various Fidel api operations on behalf of the user."
    ),
    mcps=[
        MCPServerHTTP(
            url=url,
            streamable=True,
            cache_tools_list=True,
            headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")},
        ),
    ],
    llm=llm,
    verbose=True,
    max_iter=10,
)
What's happening:
  • MCPServerHTTP connects the agent to the Fidel api MCP endpoint
  • cache_tools_list saves a tools catalog for faster subsequent runs
  • verbose helps you see what the agent is doing

Add a REPL loop with Task and Crew

python
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to perform Fidel api operations.\n")

conversation_context = ""

while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ["exit", "quit", "bye"]:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    conversation_context += f"\nUser: {user_input}\n"
    print("\nAgent is thinking...\n")

    task = Task(
        description=(
            f"Based on the conversation history:\n{conversation_context}\n\n"
            f"Current user request: {user_input}\n\n"
            f"Please help the user with their Fidel api related request."
        ),
        expected_output="A helpful response addressing the user's request",
        agent=toolkit_agent,
    )

    crew = Crew(
        agents=[toolkit_agent],
        tasks=[task],
        verbose=False,
    )

    result = crew.kickoff()
    response = str(result)

    conversation_context += f"Agent: {response}\n"
    print(f"Agent: {response}\n")
What's happening:
  • You build a simple chat loop and keep a running context
  • Each user turn becomes a Task handled by the same agent
  • Crew executes the task and returns a response

Run the application

python
if __name__ == "__main__":
    main()
What's happening:
  • Standard Python entry point so you can run python crewai_fidel_api_agent.py

Complete Code

Here's the complete code to get you started with Fidel api and CrewAI:

python
# file: crewai_fidel_api_agent.py
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter  # optional
from composio import Composio
from dotenv import load_dotenv
import os
from crewai.mcp import MCPServerHTTP

load_dotenv()

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

    # Configure LLM
    llm = LLM(
        model="gpt-5-mini",
        api_key=os.getenv("OPENAI_API_KEY"),
    )

    # Create Fidel api assistant agent
    toolkit_agent = Agent(
        role="Fidel api Assistant",
        goal="Help users interact with Fidel api through natural language commands",
        backstory=(
            "You are an expert assistant with access to Fidel api tools. "
            "You can perform various Fidel api operations on behalf of the user."
        ),
        mcps=[
            MCPServerHTTP(
                url=url,
                streamable=True,
                cache_tools_list=True,
                headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")},
            ),
        ],
        llm=llm,
        verbose=True,
        max_iter=10,
    )

    print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
    print("Try asking the agent to perform Fidel api operations.\n")

    conversation_context = ""

    while True:
        user_input = input("You: ").strip()

        if user_input.lower() in ["exit", "quit", "bye"]:
            print("\nGoodbye!")
            break

        if not user_input:
            continue

        conversation_context += f"\nUser: {user_input}\n"
        print("\nAgent is thinking...\n")

        task = Task(
            description=(
                f"Based on the conversation history:\n{conversation_context}\n\n"
                f"Current user request: {user_input}\n\n"
                f"Please help the user with their Fidel api related request."
            ),
            expected_output="A helpful response addressing the user's request",
            agent=toolkit_agent,
        )

        crew = Crew(
            agents=[toolkit_agent],
            tasks=[task],
            verbose=False,
        )

        result = crew.kickoff()
        response = str(result)

        conversation_context += f"Agent: {response}\n"
        print(f"Agent: {response}\n")

if __name__ == "__main__":
    main()

Conclusion

You now have a CrewAI agent connected to Fidel api through Composio's Tool Router. The agent can perform Fidel api operations through natural language commands. Next steps:
  • Add role-specific instructions to customize agent behavior
  • Plug in more toolkits for multi-app workflows
  • Chain tasks for complex multi-step operations

How to build Fidel api MCP Agent with another framework

FAQ

What are the differences in Tool Router MCP and Fidel api MCP?

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

Can I use Tool Router MCP with CrewAI?

Yes, you can. CrewAI 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 Fidel api tools.

Can I manage the permissions and scopes for Fidel api while using Tool Router?

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

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ASU
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai
Context
ASU
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai

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