How to integrate Cloudsmith MCP with CrewAI

This guide walks you through connecting Cloudsmith to CrewAI using the Composio tool router. By the end, you'll have a working Cloudsmith agent that can list recent packages in production repository, delete failed package versions after review, check cloudsmith repository quota usage through natural language commands. This guide will help you understand how to give your CrewAI agent real control over a Cloudsmith account through Composio's Cloudsmith MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Cloudsmith is a cloud-native artifact management platform for software packages, containers, and dependencies. It helps teams securely store, distribute, and govern packages across repositories and environments.

10 Tools

Introduction

This guide walks you through connecting Cloudsmith to CrewAI using the Composio tool router. By the end, you'll have a working Cloudsmith agent that can list recent packages in production repository, delete failed package versions after review, check cloudsmith repository quota usage through natural language commands.

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

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

Also integrate Cloudsmith with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AILlamaIndex

TL;DR

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

The Cloudsmith MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Cloudsmith account. It provides structured and secure access to your organizations, repositories, packages, vulnerabilities, audit history, quotas, and rate limits, so your agent can discover organizations, inspect repositories, search packages, review security findings, and monitor account activity on your behalf.

  • Organization and account discovery: Have your agent confirm the connected Cloudsmith user and list the organizations available to that account.
  • Repository search and inspection: Let the agent find repositories within an organization and review their configuration, visibility, usage, and supported capabilities.
  • Package search and analysis: Direct your agent to search packages by name, version, format, architecture, distribution, filename, or status, then inspect package metadata, checksums, licensing, and security state.
  • Vulnerability review: Instruct your agent to list package vulnerability scan summaries for a repository so your team can identify security concerns.
  • Usage and activity monitoring: Have your agent check storage and bandwidth quotas, review current request limits, and search audit events by action, actor, or time.

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 Cloudsmith 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 Cloudsmith 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 Cloudsmith MCP URL
6

Create a Composio Tool Router session for Cloudsmith

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

url = session.mcp.url
What's happening:
  • You create a Cloudsmith only session through Composio
  • Composio returns an MCP HTTP URL that exposes Cloudsmith 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 Cloudsmith 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=["cloudsmith"],
)
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 Cloudsmith through Composio's Tool Router. The agent can perform Cloudsmith 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 Cloudsmith action and event your agent gets out of the box.

Get Current User

Return the identity authenticated by the connected Cloudsmith API key.

Get Package

Get metadata, status, checksums, licensing, and security state for one package in a Cloudsmith repository.

Get Quota

Return current storage and bandwidth usage and allowances for a Cloudsmith namespace without inferring a billing plan name.

Get Rate Limits

Return Cloudsmith's current per-resource request limits, remaining counts, intervals, and throttling state for the authenticated principal.

Get Repository

Get configuration, visibility, usage, and capability details for one Cloudsmith repository without returning repository signing keys or certificates.

List Organizations

List Cloudsmith organizations associated with the authenticated principal so an agent can discover namespace slugs for later calls.

List Repository Vulnerabilities

List vulnerability scan summaries for packages in a Cloudsmith repository.

Search Audit Log

Search paginated audit events for a Cloudsmith namespace by event, actor, or timestamp text.

Search Packages

Search packages in a Cloudsmith repository by name, filename, version, distribution, architecture, format, or status.

Search Repositories

Search and list repositories within a Cloudsmith namespace, returning identifiers and summary state without repository signing keys.

FRAMEWORKS

How to build Cloudsmith MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Cloudsmith MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

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Claude Code logo

Claude Code

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Claude Cowork logo

Claude Cowork

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Codex logo

Codex

Use Cloudsmith MCP with Codex

OpenClaw logo

OpenClaw

Use Cloudsmith MCP with OpenClaw

Hermes logo

Hermes

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CLI logo

CLI

Use Cloudsmith MCP with CLI

Google ADK logo

Google ADK

Use Cloudsmith MCP with Google ADK

LangChain logo

LangChain

Use Cloudsmith MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Cloudsmith MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Cloudsmith MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Cloudsmith MCP with LlamaIndex

FAQ

Frequently asked questions

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

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

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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.

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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.

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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.

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