# How to integrate Respond io MCP with CrewAI ```json { "title": "How to integrate Respond io MCP with CrewAI", "toolkit": "Respond io", "toolkit_slug": "respond_io", "framework": "CrewAI", "framework_slug": "crew-ai", "url": "https://composio.dev/toolkits/respond_io/framework/crew-ai", "markdown_url": "https://composio.dev/toolkits/respond_io/framework/crew-ai.md", "updated_at": "2026-05-12T10:24:00.473Z" } ``` ## Introduction This guide walks you through connecting Respond io to CrewAI using the Composio tool router. By the end, you'll have a working Respond io agent that can add internal note to latest conversation, create a new contact named alex kim, list all channels connected to workspace through natural language commands. This guide will help you understand how to give your CrewAI agent real control over a Respond io account through Composio's Respond io MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Respond io with - [OpenAI Agents SDK](https://composio.dev/toolkits/respond_io/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/respond_io/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/respond_io/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/respond_io/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/respond_io/framework/codex) - [OpenClaw](https://composio.dev/toolkits/respond_io/framework/openclaw) - [Hermes](https://composio.dev/toolkits/respond_io/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/respond_io/framework/cli) - [Google ADK](https://composio.dev/toolkits/respond_io/framework/google-adk) - [LangChain](https://composio.dev/toolkits/respond_io/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/respond_io/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/respond_io/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/respond_io/framework/llama-index) ## TL;DR Here's what you'll learn: - Get a Composio API key and configure your Respond io connection - Set up CrewAI with an MCP enabled agent - Create a Tool Router session or standalone MCP server for Respond io - Build a conversational loop where your agent can execute Respond io 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 Respond io MCP server, and what's possible with it? The Respond io MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Respond io account. It provides structured and secure access to your customer conversation management platform, so your agent can perform actions like managing contacts, adding internal comments, creating and updating tags, and retrieving messages on your behalf. - Create and manage contacts: Easily have your agent add new customer contacts to your workspace, ensuring your CRM is always up to date. - Add internal comments to conversations: Let your agent insert internal notes into customer conversations, keeping your team informed and collaborating seamlessly. - Retrieve and organize channels: Direct your agent to list all messaging channels connected to your workspace, making it simple to audit or assign channels for support. - Tag and categorize conversations: Enable your agent to create new tags or update existing ones, helping you organize contacts and conversations for efficient follow-up. - Fetch specific messages: Ask your agent to pull up particular messages for review or context, streamlining support and follow-up actions. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `RESPOND_IO_CREATE_COMMENT` | Add internal comment to conversation | Tool to add a comment (internal note) to a contact's conversation. Use after verifying the contact identifier. | | `RESPOND_IO_CREATE_CONTACT` | Create Contact | Creates a new contact in the respond.io workspace with the specified details. The contact is identified by email, phone number, or contact ID. Supports adding profile information, language preferences, and custom fields that have been pre-configured in the workspace. | | `RESPOND_IO_CREATE_SPACE_TAG` | Create Space Tag | Creates a new tag in the Respond.io workspace for organizing and categorizing contacts and conversations. Tags help with segmentation, filtering, and workflow automation. Each tag must have a unique name within the workspace. | | `RESPOND_IO_GET_MESSAGE` | Get Message | Tool to retrieve a specific message. Use when you need the details of a message sent to or received from a contact. | | `RESPOND_IO_LIST_CHANNELS` | List channels | Tool to retrieve a list of channels connected to the workspace. Use when you need to enumerate all messaging channels with pagination support. | | `RESPOND_IO_LIST_USERS` | List users | Tool to retrieve a list of users in the workspace. Use when you need to fetch all workspace users for auditing or assignment. | | `RESPOND_IO_UPDATE_SPACE_TAG` | Update Space Tag | Updates an existing workspace tag by its current name. You can modify the tag's name, description, or emoji. Note: Color codes are not currently supported by the API and will be rejected if provided. At least one field besides currentName must be provided to update. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Respond io MCP server is an implementation of the Model Context Protocol that connects your AI agent to Respond io. It provides structured and secure access so your agent can perform Respond io 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 Respond io 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 Respond io 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 Respond io 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 Respond io **What's happening:** - You create a Respond io only session through Composio - Composio returns an MCP HTTP URL that exposes Respond io tools ```python composio_client = Composio(api_key=COMPOSIO_API_KEY) session = composio_client.create(user_id=COMPOSIO_USER_ID, toolkits=["respond_io"]) 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=["respond_io"], ) 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 Respond io through Composio's Tool Router. The agent can perform Respond io 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 Respond io MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/respond_io/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/respond_io/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/respond_io/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/respond_io/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/respond_io/framework/codex) - [OpenClaw](https://composio.dev/toolkits/respond_io/framework/openclaw) - [Hermes](https://composio.dev/toolkits/respond_io/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/respond_io/framework/cli) - [Google ADK](https://composio.dev/toolkits/respond_io/framework/google-adk) - [LangChain](https://composio.dev/toolkits/respond_io/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/respond_io/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/respond_io/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/respond_io/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. Grow your sales pipeline faster with powerful prospecting tools. - [Autobound](https://composio.dev/toolkits/autobound) - Autobound is an AI-powered sales engagement platform that crafts hyper-personalized outreach and insights. It helps sales teams boost response rates and close more deals through tailored content and recommendations. - [Better proposals](https://composio.dev/toolkits/better_proposals) - Better Proposals is a web-based tool for crafting and sending professional proposals. It helps teams impress clients and close deals faster with slick, easy-to-use templates. - [Bidsketch](https://composio.dev/toolkits/bidsketch) - Bidsketch is a proposal software that helps businesses create professional proposals quickly and efficiently. It streamlines the proposal process, saving time while boosting client win rates. - [Bolna](https://composio.dev/toolkits/bolna) - Bolna is an AI platform for building conversational voice agents. 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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 Respond io MCP? With a standalone Respond io MCP server, the agents and LLMs can only access a fixed set of Respond io tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Respond io 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 Respond io tools. ### Can I manage the permissions and scopes for Respond io while using Tool Router? Yes, absolutely. You can configure which Respond io 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 Respond io data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)