How to integrate Api ninjas MCP with CrewAI

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Introduction

This guide walks you through connecting Api ninjas to CrewAI using the Composio tool router. By the end, you'll have a working Api ninjas agent that can get real-time bitcoin price and market data, check if this email is disposable, look up bank info for this bin, fetch gold commodity price right now through natural language commands.

This guide will help you understand how to give your CrewAI agent real control over a Api ninjas account through Composio's Api ninjas 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 Api ninjas connection
  • Set up CrewAI with an MCP enabled agent
  • Create a Tool Router session or standalone MCP server for Api ninjas
  • Build a conversational loop where your agent can execute Api ninjas 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 Api ninjas MCP server, and what's possible with it?

The Api ninjas MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Api ninjas account. It provides structured and secure access to a wide array of real-time data APIs, so your agent can perform actions like fetching financial data, generating barcodes, validating emails, and looking up domains on your behalf.

  • Fetch live financial and crypto data: Instantly retrieve up-to-date prices for stocks, commodities, ETFs, and cryptocurrencies, or access earnings calendars and transcripts for informed decision-making.
  • Barcode generation on demand: Have your agent create barcode images for custom data or text, perfect for inventory, tickets, or quick sharing of encoded information.
  • Email validation and security checks: Automatically check if an email address is disposable or risky before engaging users or sending communications.
  • Bank and payment info lookup: Look up bank details using BIN numbers, helping with payment processing, fraud detection, or financial analysis.
  • Domain and DNS diagnostics: Let your agent perform DNS lookups to fetch domain records, aiding in troubleshooting or technical audits quickly and efficiently.

Supported Tools & Triggers

Tools
Generate Barcode ImageTool to generate a barcode image for specified text.
BIN LookupTool to look up bank information from a bank identification number.
Get Bitcoin Price and Market DataTool to retrieve the latest bitcoin price and 24-hour market data.
Commodity PriceTool to get real-time price for a commodity.
Crypto PriceTool to get real-time price for a cryptocurrency pair.
Check Disposable EmailTool to check whether an email address is from a disposable email provider.
DNS LookupTool to retrieve dns records for a specified domain.
Earnings CalendarTool to fetch past and upcoming earnings results for a specified ticker.
Earnings Call TranscriptTool to get the earnings call transcript for a company and quarter.
ETF InfoTool to get detailed information about an etf by ticker.
Income TaxTool to get current and historical income tax rates for a country.
IBAN LookupTool to look up and validate an international bank account number (iban).
Income Tax CalculatorTool to calculate income taxes for us and canada.
Get Inflation DataTool to get current inflation data for a country.
Interest RateTool to get current interest rates for central banks and benchmarks.
Market CapTool to get real-time market cap data for a company.
Mortgage RateTool to get current and historical mortgage rates.
Extract Nutrition InformationTool to extract nutrition information from text query.

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 Api ninjas 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 Api ninjas 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 Api ninjas MCP URL

Create a Composio Tool Router session for Api ninjas

python
composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
session = composio.create(
    user_id=os.getenv("USER_ID"),
    toolkits=["api_ninjas"],
)
url = session.mcp.url
What's happening:
  • You create a Api ninjas only session through Composio
  • Composio returns an MCP HTTP URL that exposes Api ninjas 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="Api ninjas Assistant",
    goal="Help users interact with Api ninjas through natural language commands",
    backstory=(
        "You are an expert assistant with access to Api ninjas tools. "
        "You can perform various Api ninjas 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 Api ninjas 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 Api ninjas 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 Api ninjas 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_api_ninjas_agent.py

Complete Code

Here's the complete code to get you started with Api ninjas and CrewAI:

python
# file: crewai_api_ninjas_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 Api ninjas session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["api_ninjas"],
    )
    url = session.mcp.url

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

    # Create Api ninjas assistant agent
    toolkit_agent = Agent(
        role="Api ninjas Assistant",
        goal="Help users interact with Api ninjas through natural language commands",
        backstory=(
            "You are an expert assistant with access to Api ninjas tools. "
            "You can perform various Api ninjas 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 Api ninjas 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 Api ninjas 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 Api ninjas through Composio's Tool Router. The agent can perform Api ninjas 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 Api ninjas MCP Agent with another framework

FAQ

What are the differences in Tool Router MCP and Api ninjas MCP?

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

Can I manage the permissions and scopes for Api ninjas while using Tool Router?

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

Used by agents from

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ASU
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glean
HubSpot
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Context
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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