# How to integrate Dromo MCP with CrewAI ```json { "title": "How to integrate Dromo MCP with CrewAI", "toolkit": "Dromo", "toolkit_slug": "dromo", "framework": "CrewAI", "framework_slug": "crew-ai", "url": "https://composio.dev/toolkits/dromo/framework/crew-ai", "markdown_url": "https://composio.dev/toolkits/dromo/framework/crew-ai.md", "updated_at": "2026-05-12T10:09:50.251Z" } ``` ## Introduction This guide walks you through connecting Dromo to CrewAI using the Composio tool router. By the end, you'll have a working Dromo agent that can list all spreadsheet uploads from this week, upload new customer data csv file, filter uploads with validation errors only through natural language commands. This guide will help you understand how to give your CrewAI agent real control over a Dromo account through Composio's Dromo MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Dromo with - [OpenAI Agents SDK](https://composio.dev/toolkits/dromo/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/dromo/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/dromo/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/dromo/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/dromo/framework/codex) - [OpenClaw](https://composio.dev/toolkits/dromo/framework/openclaw) - [Hermes](https://composio.dev/toolkits/dromo/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/dromo/framework/cli) - [Google ADK](https://composio.dev/toolkits/dromo/framework/google-adk) - [LangChain](https://composio.dev/toolkits/dromo/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/dromo/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/dromo/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/dromo/framework/llama-index) ## TL;DR Here's what you'll learn: - Get a Composio API key and configure your Dromo connection - Set up CrewAI with an MCP enabled agent - Create a Tool Router session or standalone MCP server for Dromo - Build a conversational loop where your agent can execute Dromo 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 Dromo MCP server, and what's possible with it? The Dromo MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Dromo account. It provides structured and secure access to your spreadsheet imports and uploads, so your agent can perform actions like listing uploads, managing import sessions, handling file uploads, and automating data onboarding on your behalf. - Retrieve all upload sessions: Quickly ask your agent to fetch and list every spreadsheet upload in your Dromo organization for easy monitoring and management. - Filter and paginate uploads: Effortlessly apply filters or paginate through large numbers of uploads to find the exact import session you need. - Headless spreadsheet file uploads: Direct your agent to upload files to Dromo's headless import, automating the data onboarding process without manual intervention. - Automate validation and transformation flows: Let your agent initiate uploads that trigger Dromo's validation and transformation pipelines, ensuring data quality and consistency. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `DROMO_CREATE_HEADLESS_IMPORT` | Create Headless Import | Tool to create a headless import in Dromo. Returns a signed upload URL for file uploads. Use this before uploading files to obtain the temporary upload URL. | | `DROMO_CREATE_IMPORT_SCHEMA` | Create Import Schema | Tool to create a new import schema in Dromo. Define fields, validation rules, and settings for data imports. Use this when setting up a new data import workflow or template. | | `DROMO_DELETE_IMPORT_SCHEMA` | Delete Import Schema | Tool to delete an import schema in Dromo. Use when you need to remove a schema definition that is no longer needed. This action is irreversible. | | `DROMO_GET_IMPORT_SCHEMA` | Get Import Schema | Tool to retrieve an import schema by ID from Dromo. Returns the complete schema definition including fields, validation rules, settings, and webhook configurations. Use this to inspect schema structure, validate field requirements, or retrieve configuration details before creating imports. | | `DROMO_LIST_IMPORT_SCHEMAS` | List Import Schemas | Tool to retrieve all import schemas configured for your Dromo organization. Use this to discover available schemas, their field definitions, validation rules, and settings before creating imports. | | `DROMO_LIST_UPLOADS` | List Uploads | Retrieves a paginated list of all file uploads stored by Dromo for your organization. Returns upload metadata including status, row counts, errors, user information, and file details. Use this to monitor import progress, track upload history, or retrieve upload IDs for further processing. | | `DROMO_UPDATE_IMPORT_SCHEMA` | Update Import Schema | Tool to update an existing import schema in Dromo. Modifies the schema definition including fields, validation rules, and settings. Use when you need to change field configurations, add/remove validators, or update import settings for an existing schema. | | `DROMO_UPLOAD_FILE_TO_HEADLESS_IMPORT` | Upload File To Headless Import | Upload a file to Dromo's headless import system using a presigned S3 URL. This action performs the actual file upload step in Dromo's headless import workflow: 1. First, create a headless import via POST to /headless/imports/ to get an upload URL 2. Then, use this action to upload the file to that URL 3. Dromo automatically processes the file once the upload completes The upload URL is valid for 30 minutes. This action performs an HTTP PUT request with the file content to the provided presigned S3 URL. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Dromo MCP server is an implementation of the Model Context Protocol that connects your AI agent to Dromo. It provides structured and secure access so your agent can perform Dromo operations on your behalf through a secure, permission-based interface. With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster. ## Step-by-step Guide ### 1. Prerequisites Before starting, make sure you have: - Python 3.9 or higher - A Composio account and API key - A Dromo connection authorized in Composio - An OpenAI API key for the CrewAI LLM - Basic familiarity with Python ### 1. Getting API Keys for OpenAI and Composio OpenAI API Key - Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) 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](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs). - Navigate to your API settings and generate a new API key. - Store this key securely as you'll need it for authentication. ### 2. Install dependencies **What's happening:** - composio connects your agent to Dromo via MCP - crewai provides Agent, Task, Crew, and LLM primitives - crewai-tools[mcp] includes MCP helpers - python-dotenv loads environment variables from .env ```bash pip install composio crewai crewai-tools[mcp] python-dotenv ``` ### 3. Set up environment variables 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 ```bash COMPOSIO_API_KEY=your_composio_api_key_here USER_ID=your_user_id_here OPENAI_API_KEY=your_openai_api_key_here ``` ### 4. Import dependencies **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 Dromo MCP URL ```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") ``` ### 5. Create a Composio Tool Router session for Dromo **What's happening:** - You create a Dromo only session through Composio - Composio returns an MCP HTTP URL that exposes Dromo tools ```python composio_client = Composio(api_key=COMPOSIO_API_KEY) session = composio_client.create(user_id=COMPOSIO_USER_ID, toolkits=["dromo"]) url = session.mcp.url ``` ### 6. Initialize the MCP Server **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. ```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, ) ``` ### 7. Create a CLI Chatloop and define the Crew **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. ```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") ``` ## Complete Code ```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=["dromo"], ) 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 Dromo through Composio's Tool Router. The agent can perform Dromo 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 ## How to build Dromo MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/dromo/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/dromo/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/dromo/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/dromo/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/dromo/framework/codex) - [OpenClaw](https://composio.dev/toolkits/dromo/framework/openclaw) - [Hermes](https://composio.dev/toolkits/dromo/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/dromo/framework/cli) - [Google ADK](https://composio.dev/toolkits/dromo/framework/google-adk) - [LangChain](https://composio.dev/toolkits/dromo/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/dromo/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/dromo/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/dromo/framework/llama-index) ## Related Toolkits - [Excel](https://composio.dev/toolkits/excel) - Microsoft Excel is a robust spreadsheet application for organizing, analyzing, and visualizing data. It's the go-to tool for calculations, reporting, and flexible data management. - [21risk](https://composio.dev/toolkits/_21risk) - 21RISK is a web app built for easy checklist, audit, and compliance management. It streamlines risk processes so teams can focus on what matters. - [Abstract](https://composio.dev/toolkits/abstract) - Abstract provides a suite of APIs for automating data validation and enrichment tasks. It helps developers streamline workflows and ensure data quality with minimal effort. - [Addressfinder](https://composio.dev/toolkits/addressfinder) - Addressfinder is a data quality platform for verifying addresses, emails, and phone numbers. It helps you ensure accurate customer and contact data every time. - [Agentql](https://composio.dev/toolkits/agentql) - Agentql is a toolkit that connects AI agents to the web using a specialized query language. It enables structured web interaction and data extraction for smarter automations. - [Agenty](https://composio.dev/toolkits/agenty) - Agenty is a web scraping and automation platform for extracting data and automating browser tasks—no coding needed. It streamlines data collection, monitoring, and repetitive online actions. - [Ambee](https://composio.dev/toolkits/ambee) - Ambee is an environmental data platform providing real-time, hyperlocal APIs for air quality, weather, and pollen. Get precise environmental insights to power smarter decisions in your apps and workflows. - [Ambient weather](https://composio.dev/toolkits/ambient_weather) - Ambient Weather is a platform for personal weather stations with a robust API for accessing local, real-time, and historical weather data. Get detailed environmental insights directly from your own sensors for smarter apps and automations. - [Anonyflow](https://composio.dev/toolkits/anonyflow) - Anonyflow is a service for encryption-based data anonymization and secure data sharing. It helps organizations meet GDPR, CCPA, and HIPAA data privacy compliance requirements. - [Api ninjas](https://composio.dev/toolkits/api_ninjas) - Api ninjas offers 120+ public APIs spanning categories like weather, finance, sports, and more. Developers use it to supercharge apps with real-time data and actionable endpoints. - [Api sports](https://composio.dev/toolkits/api_sports) - Api sports is a comprehensive sports data platform covering 2,000+ competitions with live scores and 15+ years of stats. Instantly access up-to-date sports information for analysis, apps, or chatbots. - [Apify](https://composio.dev/toolkits/apify) - Apify is a cloud platform for building, deploying, and managing web scraping and automation tools called Actors. It lets you automate data extraction and workflow tasks at scale—no infrastructure headaches. - [Autom](https://composio.dev/toolkits/autom) - Autom is a lightning-fast search engine results data platform for Google, Bing, and Brave. Developers use it to access fresh, low-latency SERP data on demand. - [Beaconchain](https://composio.dev/toolkits/beaconchain) - Beaconchain is a real-time analytics platform for Ethereum 2.0's Beacon Chain. It provides detailed insights into validators, blocks, and overall network performance. - [Big data cloud](https://composio.dev/toolkits/big_data_cloud) - BigDataCloud provides APIs for geolocation, reverse geocoding, and address validation. Instantly access reliable location intelligence to enhance your applications and workflows. - [Bigpicture io](https://composio.dev/toolkits/bigpicture_io) - BigPicture.io offers APIs for accessing detailed company and profile data. Instantly enrich your applications with up-to-date insights on 20M+ businesses. - [Bitquery](https://composio.dev/toolkits/bitquery) - Bitquery is a blockchain data platform offering indexed, real-time, and historical data from 40+ blockchains via GraphQL APIs. Get unified, reliable access to complex on-chain data for analytics, trading, and research. - [Brightdata](https://composio.dev/toolkits/brightdata) - Brightdata is a leading web data platform offering advanced scraping, SERP APIs, and anti-bot tools. It lets you collect public web data at scale, bypassing blocks and friction. - [Builtwith](https://composio.dev/toolkits/builtwith) - BuiltWith is a web technology profiler that uncovers the technologies powering any website. Gain actionable insights into analytics, hosting, and content management stacks for smarter research and lead generation. - [Byteforms](https://composio.dev/toolkits/byteforms) - Byteforms is an all-in-one platform for creating forms, managing submissions, and integrating data. It streamlines workflows by centralizing form data collection and automation. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Dromo MCP? With a standalone Dromo MCP server, the agents and LLMs can only access a fixed set of Dromo tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Dromo and many other apps based on the task at hand, all through a single MCP endpoint. ### Can I use Tool Router MCP with CrewAI? 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 Dromo tools. ### Can I manage the permissions and scopes for Dromo while using Tool Router? Yes, absolutely. You can configure which Dromo 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 Dromo data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)