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How to integrate Composio search MCP with CrewAI

Connect CrewAI to Composio search MCP. Find recent news about electric vehicles, search for top-rated hotels in paris, and more using natural language, with authentication handled for you.

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Composio search is a unified web search toolkit spanning travel, e-commerce, news, financial markets, images, and more. It lets you and your apps tap into up-to-date web data from a single, easy-to-integrate service.

21 Tools

Introduction

This guide walks you through connecting Composio search to CrewAI using the Composio tool router. By the end, you'll have a working Composio search agent that can search the web and news, find flights and hotels, search shopping results, look up SEC filings, and fetch URL content through natural language commands.

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

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

For exact tool slugs and parameter tables, see the tool catalog in the Composio docs.

Also integrate Composio search with

Claude CodeClaude CoworkOpenAI Agents SDKClaude Agent SDKGrok BotMuseCodexOpenClawHermesAtomic AgentGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexPydantic AIAutoGen

TL;DR

Here's what you'll learn:
  • Get a Composio API key and configure your Composio search connection
  • Set up CrewAI with an MCP enabled agent
  • Create a Tool Router session or standalone MCP server for Composio search
  • Build a conversational loop where your agent can execute Composio search 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 Composio search MCP server, and what's possible with it?

The Composio Search MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to Composio Search. It provides structured and secure access to web, travel, shopping, financial, news, and public filing search, so your agent can find flights and hotels, compare products, track markets, research current events, and retrieve public web content on your behalf.

  • Travel planning: Have your agent search flights, hotels, vacation rentals, and TripAdvisor recommendations for your next trip.
  • Product and deal discovery: Let the agent search Amazon and other shopping sources, compare prices, apply location preferences, and find deals.
  • Market and company research: Direct your agent to retrieve stock prices, market data, financial news, company information, and historical analysis.
  • News and web research: Instruct your agent to search current news and the wider web for relevant articles, sources, and information.
  • Filings and page retrieval: Have your agent find SEC filings such as annual, quarterly, and current reports, or extract readable text from public web pages.

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

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account and API key
  • A Composio search connection authorized in Composio
  • An OpenAI API key for the CrewAI LLM
  • Basic familiarity with Python
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 crewai crewai-tools[mcp] python-dotenv
What's happening:
  • composio connects your agent to Composio search via MCP
  • crewai provides Agent, Task, Crew, and LLM primitives
  • crewai-tools[mcp] includes MCP helpers
  • python-dotenv loads environment variables from .env
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_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
5

Import dependencies

python
import os
from composio import Composio
from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
import dotenv

dotenv.load_dotenv()

COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set")
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 Composio search MCP URL
6

Create a Composio Tool Router session for Composio search

python
composio_client = Composio(api_key=COMPOSIO_API_KEY)
session = composio_client.create(user_id=COMPOSIO_USER_ID, toolkits=["composio_search"])

url = session.mcp.url
What's happening:
  • You create a Composio search only session through Composio
  • Composio returns an MCP HTTP URL that exposes Composio search tools
7

Initialize the MCP Server

python
server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users search the internet effectively",
        backstory="You are a helpful assistant with access to search tools.",
        tools=tools,
        verbose=False,
        max_iter=10,
    )
What's Happening:
  • Server Configuration: The code sets up connection parameters including the MCP server URL, streamable HTTP transport, and Composio API key authentication.
  • MCP Adapter Bridge: MCPServerAdapter acts as a context manager that converts Composio MCP tools into a CrewAI-compatible format.
  • Agent Setup: Creates a CrewAI Agent with a defined role (Search Assistant), goal (help with internet searches), and access to the MCP tools.
  • Configuration Options: The agent includes settings like verbose=False for clean output and max_iter=10 to prevent infinite loops.
  • Dynamic Tool Usage: Once created, the agent automatically accesses all Composio Search tools and decides when to use them based on user queries.
8

Create a CLI Chatloop and define the Crew

python
print("Chat started! Type 'exit' or 'quit' to end.\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"Conversation history:\n{conversation_context}\n\n"
            f"Current request: {user_input}"
        ),
        expected_output="A helpful response addressing the user's request",
        agent=agent,
    )

    crew = Crew(agents=[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:
  • Interactive CLI Setup: The code creates an infinite loop that continuously prompts for user input and maintains the entire conversation history in a string variable.
  • Input Validation: Empty inputs are ignored to prevent processing blank messages and keep the conversation clean.
  • Context Building: Each user message is appended to the conversation context, which preserves the full dialogue history for better agent responses.
  • Dynamic Task Creation: For every user input, a new Task is created that includes both the full conversation history and the current request as context.
  • Crew Execution: A Crew is instantiated with the agent and task, then kicked off to process the request and generate a response.
  • Response Management: The agent's response is converted to a string, added to the conversation context, and displayed to the user, maintaining conversational continuity.

Complete Code

Here's the complete code to get you started with Composio search and CrewAI:

python
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter
from composio import Composio
from dotenv import load_dotenv
import os

load_dotenv()

GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not GOOGLE_API_KEY:
    raise ValueError("GOOGLE_API_KEY is not set in the environment.")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set in the environment.")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set in the environment.")

# Initialize Composio and create a session
composio = Composio(api_key=COMPOSIO_API_KEY)
session = composio.create(
    user_id=COMPOSIO_USER_ID,
    toolkits=["composio_search"],
)
url = session.mcp.url

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

server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users with internet searches",
        backstory="You are an expert assistant with access to Composio Search tools.",
        tools=tools,
        llm=llm,
        verbose=False,
        max_iter=10,
    )

    print("Chat started! Type 'exit' or 'quit' to end.\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"Conversation history:\n{conversation_context}\n\n"
                f"Current request: {user_input}"
            ),
            expected_output="A helpful response addressing the user's request",
            agent=agent,
        )

        crew = Crew(agents=[agent], tasks=[task], verbose=False)
        result = crew.kickoff()
        response = str(result)

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

Conclusion

You now have a CrewAI agent connected to Composio search through Composio's Tool Router. The agent can perform Composio search 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
TOOLS

Supported Tools

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

Amazon Product Search

Search Amazon products across international marketplaces.

Composio DuckDuckGo Search

The DuckDuckGoSearch class utilizes the Composio DuckDuckGo Search API to perform searches, focusing on web information and details.

Composio Google Events Search

Search for upcoming events, concerts, festivals, conferences, and other activities.

Composio Similarlinks

Find links similar to a supplied URL using Exa, with optional domain, date, category and result-count filters.

Fetch URL Content

Fetch and extract clean, readable page text (markdown) from public web pages (HTML content) using the Exa API.

Composio Finance Search

Search Google Finance for stock quotes, indices, cryptocurrency prices, exchange rates, company financials and related news.

Flight Search

Search flights using a natural-language route or structured airport codes and dates.

Composio Google Maps Search

Search Google Maps for places by query, optionally using map coordinates and a pagination offset.

Groq Chat Completion

Generate chat completions using Groq models for tasks such as question answering, content generation, coding, summarization and translation.

Hotel Search

Search hotels and vacation rentals by location and stay dates, with price, class, cancellation and localization filters.

Composio Image Search

Search Google Images for image metadata and URLs, including original and thumbnail links.

Composio News Search

Search Google News results by query, time window, country and language.

NPPES NPI Registry Lookup

Lookup US healthcare provider details from the CMS NPI Registry (NPPES) using an NPI number or search filters.

Composio Scholar Search

Search Google Scholar for scholarly articles.

Composio SEC EDGAR Filings Search

Retrieve recent SEC EDGAR filing metadata for a company by ticker or CIK, optionally filtering by form type and constructing primary document and index URLs.

Composio Shopping Search

Search for products with advanced price filtering, location targeting, and deal discovery.

Composio LLM Search

Search a broad range of content using the Tavily API, with options for search depth, images, direct answers, domain filters, and the number of results.

Composio Trends Search

Search Google Trends for interest over time, regional comparisons, related topics, and related queries.

TripAdvisor Travel Search

Search TripAdvisor for attractions, restaurants, hotels, tours, and other travel information without a connected TripAdvisor account.

Walmart Product Search

Search Walmart products with optional minimum and maximum price filters.

Composio Web Search

Search the web using Exa's answer API, returning an AI-generated answer and source citations.

FRAMEWORKS

How to build Composio search MCP Agent with another framework

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Claude Agent SDK logo

Claude Agent SDK

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Grok Bot logo

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Muse logo

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Codex logo

Codex

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OpenClaw logo

OpenClaw

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Hermes logo

Hermes

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Atomic Agent logo

Atomic Agent

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Google ADK logo

Google ADK

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LangChain logo

LangChain

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Vercel AI SDK logo

Vercel AI SDK

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Mastra AI logo

Mastra AI

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LlamaIndex logo

LlamaIndex

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Pydantic AI logo

Pydantic AI

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AutoGen logo

AutoGen

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FAQ

Frequently asked questions

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