How to integrate Companyenrich MCP with CrewAI

This guide walks you through connecting Companyenrich to CrewAI using the Composio tool router. By the end, you'll have a working Companyenrich agent that can enrich openai company profile by domain, find companies similar to stripe, search cybersecurity startups in berlin through natural language commands. This guide will help you understand how to give your CrewAI agent real control over a Companyenrich account through Composio's Companyenrich MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Companyenrich

Api Key

Companyenrich is a company data API for enrichment, search, and similar company discovery. Use it to turn domains or company names into clean business profiles fast.

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Introduction

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

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

Also integrate Companyenrich with

OpenAI Agents SDK Claude Agent SDK Claude Code Claude Cowork Codex OpenClaw Hermes CLI Google ADK LangChain Vercel AI SDK Mastra AI LlamaIndex

TL;DR

Here's what you'll learn:

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

The Companyenrich MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Companyenrich account. It provides structured and secure access so your agent can perform Companyenrich operations on your behalf.

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:

Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Step by step08 STEPS

Prerequisites

Before starting, make sure you have:

Python 3.9 or higher
A Composio account and API key
A Companyenrich 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[mcp] python-dotenv

What's happening:

composio connects your agent to Companyenrich via MCP
crewai provides Agent, Task, Crew, and LLM primitives
crewai-tools[mcp] 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

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 Companyenrich MCP URL

Create a Composio Tool Router session for Companyenrich

python

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

url = session.mcp.url

What's happening:

You create a Companyenrich only session through Composio
Composio returns an MCP HTTP URL that exposes Companyenrich tools

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.

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 Companyenrich 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=["companyenrich"],
)
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 Companyenrich through Composio's Tool Router. The agent can perform Companyenrich 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 Companyenrich action and event your agent gets out of the box.

Autocomplete Companies

Returns a list of companies matching the given partial domain name.

Autocomplete Keywords

Lookup keywords for use in company search filters.

Autocomplete Positions

Lookup positions/job titles for use in people search filters.

Autocomplete Technologies

Lookup technologies for use in company search filters.

Count companies matching search criteria

Returns the total count of companies matching the given search criteria without retrieving the actual results.

Count Similar Companies

Tool to count the total number of similar companies matching the given search criteria without retrieving the actual results.

Create people search export job

Creates an asynchronous search export job for up to 50,000 people.

Create search export job

Creates an asynchronous search export job for company data.

Enrich company by domain

Enriches a company using its domain name as lookup parameter.

Enrich company by properties

Enriches a company using its properties.

Batch Enrich Companies

Enriches a list of companies using their domain names.

Find Similar Companies

Tool to find similar companies to the given company by domain.

Get Bulk Enrichment Job Status

Returns the current status of a bulk enrichment job.

Get Company Workforce

Returns workforce insights for a single company.

Get Country by Code

Tool to search for a country by its ISO 3166-1 alpha-2 code.

Get Current User

Returns information about the authenticated user, including their API key, credit balance, and account capabilities.

Get Job Details

Returns details for a specific job by ID.

Get People Search Export Job Status

Returns the current status of a person search export job.

Get Regions

Tool to get all available regions.

Get search export job status

Returns the current status of a search export job.

List all jobs

Returns a paginated list of all jobs (bulk enrichment, etc.

List bulk enrichment jobs

Returns a paginated list of all bulk enrichment jobs for the authenticated user.

List Industries

Obtain a list of all company industries.

List Person Search Export Jobs

Returns a paginated list of all person search export jobs for the authenticated user.

List search export jobs

Returns a paginated list of all search export jobs for the authenticated user.

Lookup Person by Email

Look up a person by email address.

Search people with cursor pagination

Searches people based on given criteria using cursor-based pagination.

Search cities by name or country

Search for cities by name or country codes.

Search companies by criteria

Searches companies based on given criteria.

Search Countries

Tool to search countries by name.

Search People

Searches people based on given criteria using page-based pagination.

Search States

Tool to search states by name or country codes.

FRAMEWORKS

How to build Companyenrich MCP Agent with another framework

OpenAI Agents SDK

Use Companyenrich MCP with OpenAI Agents SDK

Claude Agent SDK

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Claude Code

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Claude Cowork

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Codex

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OpenClaw

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Hermes

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CLI

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Google ADK

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LangChain

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Vercel AI SDK

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Mastra AI

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LlamaIndex

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FAQ

Frequently asked questions

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

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 Companyenrich tools.

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

Start with Companyenrich.It takes 30 seconds.

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

Start building

Customer stories

Teams ship real agents on Composio

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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

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

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

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

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

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

Co-Founder, Ingram Technologies

How to integrate Companyenrich MCP with CrewAI

Connect Companyenrich without auth hassles

Introduction

Also integrate Companyenrich with

TL;DR

What is CrewAI?

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

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

How the Composio SDK works

Step-by-step Guide

Prerequisites

Getting API Keys for OpenAI and Composio

Install dependencies

Set up environment variables

Import dependencies

Create a Composio Tool Router session for Companyenrich

Initialize the MCP Server

Create a CLI Chatloop and define the Crew

Complete Code

Conclusion

Supported Tools

How to build Companyenrich MCP Agent with another framework

OpenAI Agents SDK

Claude Agent SDK

Claude Code

Claude Cowork

Codex

OpenClaw

Hermes

CLI

Google ADK

LangChain

Vercel AI SDK

Mastra AI

LlamaIndex

Explore Other Toolkits

Excel

21risk

Abstract

Addressfinder

Frequently asked questions

What are the differences in Tool Router MCP and Companyenrich MCP?+

Can I use Tool Router MCP with CrewAI?+

Can I manage the permissions and scopes for Companyenrich while using Tool Router?+

How safe is my data with Composio Tool Router?+

Start with Companyenrich.It takes 30 seconds.

Teams ship real agents on Composio