How to integrate Composio search MCP with OpenAI Agents SDK

Framework Integration Gradient
Composio search Logo
open-ai-agents-sdk Logo
divider

Introduction

This guide walks you through connecting Composio search to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Composio search agent that can find recent news about electric vehicles, search for top-rated hotels in paris, get latest stock info for apple, show upcoming concerts in san francisco through natural language commands.

This guide will help you understand how to give your OpenAI Agents SDK 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.

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Install the necessary dependencies
  • Initialize Composio and create a Tool Router session for Composio search
  • Configure an AI agent that can use Composio search as a tool
  • Run a live chat session where you can ask the agent to perform Composio search operations

What is open-ai-agents-sdk?

The OpenAI Agents SDK is a lightweight framework for building AI agents that can use tools and maintain conversation state. It provides a simple interface for creating agents with hosted MCP tool support.

Key features include:

  • Hosted MCP Tools: Connect to external services through hosted MCP endpoints
  • SQLite Sessions: Persist conversation history across interactions
  • Simple API: Clean interface with Agent, Runner, and tool configuration
  • Streaming Support: Real-time response streaming for interactive applications

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 the entire Composio Search suite. It provides structured and secure access to powerful web, travel, shopping, news, academic, and financial search tools, so your agent can perform actions like searching the web, finding events, locating places, pulling news, and fetching academic research on your behalf.

  • Comprehensive web and news search: Instantly ask your agent to fetch up-to-date web pages, breaking news, or current events using Google, DuckDuckGo, or news-specific search APIs.
  • Travel and local discovery: Let your agent find nearby hotels, flights, events, or map locations using Google Maps and events search for seamless travel planning and local exploration.
  • E-commerce and product lookup: Have your agent search for products, deals, and reviews across major retailers like Amazon and Walmart to help you shop smarter and faster.
  • Financial and market data retrieval: Direct your agent to pull real-time stock information, financial news, and market trends with just a query—no manual research needed.
  • Academic and scholarly research: Empower your agent to find relevant academic papers, citations, and scholarly articles using Google Scholar and Exa Answer for research-heavy tasks.

Supported Tools & Triggers

Tools
Composio DuckDuckGo SearchThe duckduckgosearch class utilizes the composio duckduckgo search api to perform searches, focusing on web information and details.
Composio Google Events SearchThe eventsearch class enables scraping of google events search queries.
Exa AnswerGet answers with citations using the exa api.
Composio SimilarlinksPerform a search to find similar links and retrieve a list of relevant results.
Composio Finance SearchThe financesearch class utilizes the composio finance search api to conduct financial searches, focusing on financial data and stock information.
Composio Google Maps SearchThe googlemapssearch class performs a location-specific search using the composio goolge maps search api.
Composio Image SearchThe imagesearch class performs an image search using the composio image search api, to target image data and information.
Composio News SearchThe newssearch class performs a news-specific search using the composio news search api.
Composio Scholar SearchScholar api allows you to scrape results from a google scholar search query.
Composio Google SearchPerform a google search using the composio google search api.
Composio Shopping SearchThe shoppingsearch class performs a product search using the composio shopping search api.
Composio LLM SearchThe composio llm search class serves as a gateway to the composio llm search api, allowing users to perform searches across a broad range of content with multiple filtering options.
Composio Trends SearchThe trendssearch class performs a trend search using the google trends search api, to target trend data and information.

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:
  • Composio API Key and OpenAI API Key
  • Primary know-how of OpenAI Agents SDK
  • A live Composio search project
  • Some knowledge of Python or Typescript

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

Install dependencies

pip install composio_openai_agents openai-agents python-dotenv

Install the Composio SDK and the OpenAI Agents SDK.

Set up environment variables

bash
OPENAI_API_KEY=sk-...your-api-key
COMPOSIO_API_KEY=your-api-key
USER_ID=composio_user@gmail.com

Create a .env file and add your OpenAI and Composio API keys.

Import dependencies

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession
What's happening:
  • You're importing all necessary libraries.
  • The Composio and OpenAIAgentsProvider classes are imported to connect your OpenAI agent to Composio tools like Composio search.

Set up the Composio instance

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())
What's happening:
  • load_dotenv() loads your .env file so OPENAI_API_KEY and COMPOSIO_API_KEY are available as environment variables.
  • Creating a Composio instance using the API Key and OpenAIAgentsProvider class.

Create a Tool Router session

# Create a Composio search Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["composio_search"]
)

mcp_url = session.mcp.url

What is happening:

  • You give the Tool Router the user id and the toolkits you want available. Here, it is only composio_search.
  • The router checks the user's Composio search connection and prepares the MCP endpoint.
  • The returned session.mcp.url is the MCP URL that your agent will use to access Composio search.
  • This approach keeps things lightweight and lets the agent request Composio search tools only when needed during the conversation.

Configure the agent

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Composio search. "
        "Help users perform Composio search operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)
What's happening:
  • We're creating an Agent instance with a name, model (gpt-5), and clear instructions about its purpose.
  • The agent's instructions tell it that it can access Composio search and help with queries, inserts, updates, authentication, and fetching database information.
  • The tools array includes a HostedMCPTool that connects to the MCP server URL we created earlier.
  • The headers dict includes the Composio API key for secure authentication with the MCP server.
  • require_approval: 'never' means the agent can execute Composio search operations without asking for permission each time, making interactions smoother.

Start chat loop and handle conversation

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())
What's happening:
  • The program prints a session URL that you visit to authorize Composio search.
  • After authorization, the chat begins.
  • Each message you type is processed by the agent using Runner.run().
  • The responses are printed to the console, and conversations are saved locally using SQLite.
  • Typing exit, quit, or q cleanly ends the chat.

Complete Code

Here's the complete code to get you started with Composio search and open-ai-agents-sdk:

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())

# Create Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["composio_search"]
)
mcp_url = session.mcp.url

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Composio search. "
        "Help users perform Composio search operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())

Conclusion

This was a starter code for integrating Composio search MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Composio search.

Key features:

  • Hosted MCP tool integration through Composio's Tool Router
  • SQLite session persistence for conversation history
  • Simple async chat loop for interactive testing
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.

How to build Composio search MCP Agent with another framework

FAQ

What are the differences in Tool Router MCP and Composio search MCP?

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

Can I use Tool Router MCP with OpenAI Agents SDK?

Yes, you can. OpenAI Agents SDK 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 Composio search tools.

Can I manage the permissions and scopes for Composio search while using Tool Router?

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

Used by agents from

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

Never worry about agent reliability

We handle tool reliability, observability, and security so you never have to second-guess an agent action.