How to integrate OneUp MCP with CrewAI

This guide walks you through connecting OneUp to CrewAI using the Composio tool router. By the end, you'll have a working OneUp agent that can create social posts, upload media, edit scheduled posts, comment on posts, and analyze engagement through natural language commands. This guide will help you understand how to give your CrewAI agent real control over a OneUp account through Composio's OneUp MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Api Key

OneUp is a social media management platform for scheduling posts, comments, accounts, media, and analytics. Use it to manage multiple social networks from one place and keep publishing consistent.

27 Tools

Introduction

This guide walks you through connecting OneUp to CrewAI using the Composio tool router. By the end, you'll have a working OneUp agent that can create social posts, upload media, edit scheduled posts, comment on posts, and analyze engagement through natural language commands.

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

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

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TL;DR

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

The OneUp MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your OneUp account. It provides structured and secure access to your social accounts, posts, comments, media, and analytics, so your agent can schedule content, manage conversations, review performance, organize accounts, and discover trending sounds on your behalf.

  • Social post creation and scheduling: Have your agent create text, image, or video posts as drafts, scheduled content, or timeslot posts for selected social accounts.
  • Post management and recovery: Direct your agent to list posts, edit or delete scheduled content, and reschedule failed posts for a future date and time.
  • Comment and review management: Let the agent refresh and review comment threads, publish comments and replies, delete comments, and check Google Business Profile reviews.
  • Social and advertising analytics: Instruct your agent to review account performance, audience demographics, individual content results, and Meta Ads analytics, or request updated analytics across connected accounts.
  • Account and content discovery: Have your agent check connected account health, browse account categories, find Instagram or TikTok trending sounds, and list Pinterest boards or YouTube playlists.

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 OneUp 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 OneUp 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 OneUp MCP URL
6

Create a Composio Tool Router session for OneUp

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

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

Comment On Post

Publish a new top-level comment on a social post through a connected OneUp social account.

Create Image Post

Create a scheduled, timeslot, or draft image post for selected OneUp social accounts.

Create Media Upload URL

Create a temporary OneUp media upload URL and return instructions for a separate direct upload.

Create Text Post

Create a scheduled, timeslot, or draft text post for selected OneUp social accounts.

Create Video Post

Create a scheduled, timeslot, or draft video post for selected OneUp social accounts.

Delete Comment

Permanently and irreversibly delete a social-platform comment and its local OneUp record.

Delete Scheduled Post

Permanently and irreversibly delete an unpublished scheduled OneUp post.

Edit Scheduled Post

Replace the content and optionally the title of a scheduled OneUp post.

Get Analytics Overview

Get account-level overview metrics and ranked performance for a connected account on a supported social platform.

Get Audience Demographics

Get audience demographics for a connected Facebook, Instagram, TikTok, or YouTube account for a preset or custom reporting period.

Get Content Analytics

Get per-post, Reel, or Story analytics for a connected account on a supported social platform.

Get Google Business Reviews

Get Google Business Profile reviews and aggregate rating information for a connected account or location.

Get Meta Ads Analytics

Get campaign, ad-set, or individual-ad analytics for a connected Meta Ads account.

List Categories

List OneUp categories used to group connected social accounts.

List Category Accounts

List social accounts assigned to a OneUp category.

List Comment Replies

Fetch child replies for a parent social-platform comment.

List Comment Threads

List social posts with top-level comments and child replies in the requested order, one page at a time.

List Instagram Trending Sounds

Search Instagram trending sounds for a Facebook-connected Instagram Business or Creator account.

List Pinterest Boards

List boards available to a connected Pinterest username for post targeting.

List Posts

List scheduled, published, or failed OneUp posts, one page at a time.

List Social Accounts

List all connected OneUp social accounts and their connection health.

List TikTok Trending Sounds

Get TikTok trending commercial sounds for a documented country, period, genre, and connected TikTok account.

List YouTube Playlists

List playlists for a connected YouTube channel.

Refresh Analytics

Start a background refresh of analytics for all connected social accounts.

Refresh Comments

Start a background refresh of comments from connected social platforms.

Reply To Comment

Publish a direct reply to an existing social-platform comment.

Reschedule Failed Post

Move a failed post back into the schedule at a future date and time.

FAQ

Frequently asked questions

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

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

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