# How to integrate Reply MCP with CrewAI ```json { "title": "How to integrate Reply MCP with CrewAI", "toolkit": "Reply", "toolkit_slug": "reply", "framework": "CrewAI", "framework_slug": "crew-ai", "url": "https://composio.dev/toolkits/reply/framework/crew-ai", "markdown_url": "https://composio.dev/toolkits/reply/framework/crew-ai.md", "updated_at": "2026-05-12T10:23:54.555Z" } ``` ## Introduction This guide walks you through connecting Reply to CrewAI using the Composio tool router. By the end, you'll have a working Reply agent that can list all active email campaigns this week, get contacts in your 'leads q3' list, show all available email templates through natural language commands. This guide will help you understand how to give your CrewAI agent real control over a Reply account through Composio's Reply MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Reply with - [OpenAI Agents SDK](https://composio.dev/toolkits/reply/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/reply/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/reply/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/reply/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/reply/framework/codex) - [OpenClaw](https://composio.dev/toolkits/reply/framework/openclaw) - [Hermes](https://composio.dev/toolkits/reply/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/reply/framework/cli) - [Google ADK](https://composio.dev/toolkits/reply/framework/google-adk) - [LangChain](https://composio.dev/toolkits/reply/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/reply/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/reply/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/reply/framework/llama-index) ## TL;DR Here's what you'll learn: - Get a Composio API key and configure your Reply connection - Set up CrewAI with an MCP enabled agent - Create a Tool Router session or standalone MCP server for Reply - Build a conversational loop where your agent can execute Reply 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 Reply MCP server, and what's possible with it? The Reply MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Reply.io account. It provides structured and secure access to your sales engagement platform, so your agent can create and manage lists, fetch campaign schedules, organize contacts, and monitor outreach performance for you. - Personal list creation and management: Easily instruct your agent to create, organize, or delete personal contact lists to streamline your outreach workflow. - Contact organization and retrieval: Have your agent fetch contacts within specific lists, helping you target and personalize campaigns more effectively. - Campaign and schedule insights: Ask your agent to retrieve all campaign schedules or see which campaigns a specific contact belongs to, giving you up-to-date visibility into your outreach pipeline. - Email account and template discovery: Let your agent pull a list of available email accounts or fetch your personal, team, and community templates for quick access while composing new campaigns. - Blacklist monitoring and management: Direct your agent to retrieve the full list of blacklisted domains and emails, so you can ensure compliance and maintain deliverability standards with ease. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `REPLY_CREATE_LIST` | Create Personal List | Tool to add a new personal list on the People page. Use when you need to organize contacts into a custom list. | | `REPLY_DELETE_EMAIL_ACCOUNT` | Delete Email Account | Tool to delete a specific email account. Use when you need to remove an existing email account identified by its ID. | | `REPLY_DELETE_LIST_BY_ID` | Delete List By ID | Tool to delete a list by its ID. Use when you need to remove a personal list you own. | | `REPLY_DELETE_SEQUENCE` | Delete Sequence | Tool to delete a sequence. Use after confirming the sequence exists to remove it permanently. | | `REPLY_DELETE_USER` | Delete User | Tool to delete a user. Use after confirming the user exists to remove them permanently. | | `REPLY_GENERATE_ULID` | Generate ULID | Generate ULID | | `REPLY_GET_ALL_LISTS` | Get All Lists | Tool to retrieve all available people lists. Use when you need to list all lists in your Reply account. | | `REPLY_GET_BLACKLIST_ALL` | Get full blacklist of domains and emails | Tool to retrieve the full list of blacklisted domains and emails. Use after confirming updates to the blacklist when you need a complete view. | | `REPLY_GET_CAMPAIGN_SCHEDULES_ALL` | Get all campaign schedules | Retrieves all campaign schedules from Reply.io, including the default schedule and any user-created schedules. Each schedule contains timezone settings, daily timing configurations (mainTimings), and follow-up timings. Use this to view available schedules before assigning one to a campaign or to audit existing schedule configurations. | | `REPLY_GET_CAMPAIGNS_FOR_CONTACT` | Get Campaigns For Contact | Tool to retrieve campaigns a contact belongs to by contact ID. Use when you need to list all sequences (campaigns) associated with a specific contact. | | `REPLY_GET_CONTACTS_IN_LIST_BY_ID` | Get Contacts in List by ID | Tool to retrieve contacts in a specific personal list. Use after obtaining the list ID when you need a paginated set of contacts for that list. | | `REPLY_GET_LIST_BY_ID` | Get List by ID | Tool to return a specific people list by its ID. Use after you know the list ID and need its details. | | `REPLY_GET_TEMPLATES_LIST` | Get templates list | Retrieves all email templates from Reply.io, including user-created, team-shared, organization-wide, and community templates. Use this to browse available templates before sending emails or creating campaigns. No parameters required - returns all accessible templates for the authenticated user. | | `REPLY_LIST_CAMPAIGNS` | List Campaigns | Tool to list all campaigns (sequences). Use when you need a paginated list of campaigns. | | `REPLY_LIST_CONTACTS_BASIC` | List Contacts Basic | Tool to list contacts. Use when verifying API access and gathering contact IDs. | | `REPLY_LIST_EMAIL_ACCOUNTS` | Reply.io List Email Accounts | Tool to list all email accounts. Use when you need to retrieve email accounts page by page. | | `REPLY_MARK_CONTACT_AS_FINISHED` | Mark Contact As Finished | Marks a contact (by email) or all contacts under a domain as finished in all Reply.io campaigns. Use this tool to stop outreach for contacts who have been successfully engaged or should no longer receive campaign messages. - When using 'email': The specific contact must exist and be enrolled in at least one campaign. - When using 'domain': Marks all contacts with that email domain as finished (succeeds even if no contacts match). Note: Provide exactly one of 'email' or 'domain', not both. | | `REPLY_MARK_CONTACT_AS_REPLIED` | Mark Contact as Replied | Tool to mark a contact as replied in all campaigns by email or domain. Use after confirming the contact has responded. | | `REPLY_MOVE_CONTACTS_TO_LISTS` | Move Contacts to Lists | Tool to move one or more contacts to specified lists. Use when reorganizing contacts across lists after verifying contact and list IDs. | | `REPLY_REMOVE_DOMAIN_FROM_BLACKLIST` | Remove Domain from Blacklist | Tool to remove the specified domain from the blacklist. Use when you need to allow sending to that domain again. | | `REPLY_SEARCH_CONTACTS` | Search Contacts by Email | Tool to search contacts by email. Use when you need to find existing contact IDs for update tests. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Reply MCP server is an implementation of the Model Context Protocol that connects your AI agent to Reply. It provides structured and secure access so your agent can perform Reply 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 Reply 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 Reply 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 Reply 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 Reply **What's happening:** - You create a Reply only session through Composio - Composio returns an MCP HTTP URL that exposes Reply tools ```python composio_client = Composio(api_key=COMPOSIO_API_KEY) session = composio_client.create(user_id=COMPOSIO_USER_ID, toolkits=["reply"]) 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=["reply"], ) 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 Reply through Composio's Tool Router. The agent can perform Reply 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 Reply MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/reply/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/reply/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/reply/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/reply/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/reply/framework/codex) - [OpenClaw](https://composio.dev/toolkits/reply/framework/openclaw) - [Hermes](https://composio.dev/toolkits/reply/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/reply/framework/cli) - [Google ADK](https://composio.dev/toolkits/reply/framework/google-adk) - [LangChain](https://composio.dev/toolkits/reply/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/reply/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/reply/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/reply/framework/llama-index) ## Related Toolkits - [Aeroleads](https://composio.dev/toolkits/aeroleads) - Aeroleads is a B2B lead generation platform for finding business emails and phone numbers. 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It helps businesses boost customer trust while stopping spam, fraud, and robocalls. - [Callingly](https://composio.dev/toolkits/callingly) - Callingly is a lead response management platform that automates immediate call and text follow-ups with new leads. It helps sales teams boost response speed and close more deals by connecting seamlessly with CRMs and lead sources. - [Callpage](https://composio.dev/toolkits/callpage) - Callpage is a lead capture platform that lets businesses instantly connect with website visitors via callback. It boosts lead generation and increases your sales conversion rates. - [Clearout](https://composio.dev/toolkits/clearout) - Clearout is an AI-powered service for verifying, finding, and enriching email addresses. It boosts deliverability and helps you discover high-quality leads effortlessly. - [Clientary](https://composio.dev/toolkits/clientary) - Clientary is a platform for managing clients, invoices, projects, proposals, and more. 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Enhance outreach with automated exports, email verification, and CRM enrichment. - [Freshdesk](https://composio.dev/toolkits/freshdesk) - Freshdesk is customer support software with ticketing and automation tools. It helps teams streamline helpdesk operations for faster, better customer support. - [Fullenrich](https://composio.dev/toolkits/fullenrich) - FullEnrich is a B2B contact enrichment platform that aggregates emails and phone numbers from 15+ data vendors. Instantly find and verify lead contact data to boost your outreach. - [Gatherup](https://composio.dev/toolkits/gatherup) - GatherUp is a customer feedback and online review management platform. It helps businesses boost their reputation by streamlining how they collect and manage customer feedback. - [Getprospect](https://composio.dev/toolkits/getprospect) - Getprospect is a business email discovery tool with LinkedIn integration. Use it to quickly find and verify professional email addresses. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Reply MCP? With a standalone Reply MCP server, the agents and LLMs can only access a fixed set of Reply tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Reply 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 Reply tools. ### Can I manage the permissions and scopes for Reply while using Tool Router? Yes, absolutely. You can configure which Reply 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 Reply data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)