# How to integrate Callerapi MCP with CrewAI ```json { "title": "How to integrate Callerapi MCP with CrewAI", "toolkit": "Callerapi", "toolkit_slug": "callerapi", "framework": "CrewAI", "framework_slug": "crew-ai", "url": "https://composio.dev/toolkits/callerapi/framework/crew-ai", "markdown_url": "https://composio.dev/toolkits/callerapi/framework/crew-ai.md", "updated_at": "2026-05-12T10:04:49.906Z" } ``` ## Introduction This guide walks you through connecting Callerapi to CrewAI using the Composio tool router. By the end, you'll have a working Callerapi agent that can check if this phone number is flagged as spam, retrieve carrier and business info for a caller, show your callerapi credit usage this month through natural language commands. This guide will help you understand how to give your CrewAI agent real control over a Callerapi account through Composio's Callerapi MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Callerapi with - [OpenAI Agents SDK](https://composio.dev/toolkits/callerapi/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/callerapi/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/callerapi/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/callerapi/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/callerapi/framework/codex) - [OpenClaw](https://composio.dev/toolkits/callerapi/framework/openclaw) - [Hermes](https://composio.dev/toolkits/callerapi/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/callerapi/framework/cli) - [Google ADK](https://composio.dev/toolkits/callerapi/framework/google-adk) - [LangChain](https://composio.dev/toolkits/callerapi/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/callerapi/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/callerapi/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/callerapi/framework/llama-index) ## TL;DR Here's what you'll learn: - Get a Composio API key and configure your Callerapi connection - Set up CrewAI with an MCP enabled agent - Create a Tool Router session or standalone MCP server for Callerapi - Build a conversational loop where your agent can execute Callerapi 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 Callerapi MCP server, and what's possible with it? The Callerapi MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Callerapi account. It provides structured and secure access to caller identification and reputation data, so your agent can perform actions like verifying phone numbers, checking caller reputation, retrieving business and carrier details, and monitoring account usage on your behalf. - Detailed phone number lookup: Instantly retrieve information about any phone number, including reputation, business association, carrier, and FTC complaints. - Reputation and fraud assessment: Empower your agent to check if a phone number might be flagged for spam, robocalls, or fraud, helping you screen and validate callers. - Business and carrier identification: Have your agent fetch in-depth business and carrier details for a given number to strengthen trust and context in communications. - HLR (Home Location Register) checks: Enable your agent to request HLR data for deeper carrier and number status insights, including ported or roaming status. - Account usage monitoring: Let your agent access your Callerapi user profile to monitor credit usage, monthly allocations, and remaining balance, keeping you informed about your API consumption. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `CALLERAPI_DISPATCH_REPORTS_MANUALLY` | Dispatch Reports Manually | Tool to manually trigger today's spam reports webhook delivery for enterprise clients. Use when an immediate webhook dispatch of spam complaint reports is needed. This endpoint is restricted to enterprise accounts only. | | `CALLERAPI_GET_PHONE_NUMBER_INFORMATION` | Get Phone Number Information | Tool to retrieve detailed information about a specific phone number, including reputation, business and carrier details, and FTC complaints. Use when the number is in E.164 format and set hlr=true to include HLR data (adds 1-3 seconds to response). | | `CALLERAPI_GET_USER_INFORMATION` | Get User Information | Tool to retrieve information about the authenticated user, including email and credit usage details. Use after authentication to fetch current credits spent, monthly allocation, and credits left. | | `CALLERAPI_LIST_WEBHOOK_SUBSCRIPTIONS` | List Webhook Subscriptions | Tool to list all webhook subscriptions for daily spam reports. Enterprise clients only. Use to retrieve all configured webhook endpoints that receive spam complaint notifications. | | `CALLERAPI_SUBSCRIBE_DAILY_REPORTS` | Subscribe to Daily Spam Reports | Tool to subscribe to daily spam report webhooks for enterprise clients. Instead of polling, receive webhook deliveries with spam complaint data daily. Use when you want to set up automated daily reports for spam complaints. | | `CALLERAPI_TEST_WEBHOOK` | Test Webhook | Tool to send a sample webhook payload to test your webhook endpoint integration. Use to validate webhook signature verification and endpoint configuration. Enterprise clients only. | | `CALLERAPI_UNSUBSCRIBE_DAILY_REPORTS` | Unsubscribe from Daily Reports | Tool to unsubscribe from daily spam report webhooks. Use when you need to stop receiving daily reports at a specific webhook URL. Enterprise clients only. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Callerapi MCP server is an implementation of the Model Context Protocol that connects your AI agent to Callerapi. It provides structured and secure access so your agent can perform Callerapi 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 Callerapi 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 Callerapi 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 Callerapi 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 Callerapi **What's happening:** - You create a Callerapi only session through Composio - Composio returns an MCP HTTP URL that exposes Callerapi tools ```python composio_client = Composio(api_key=COMPOSIO_API_KEY) session = composio_client.create(user_id=COMPOSIO_USER_ID, toolkits=["callerapi"]) 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=["callerapi"], ) 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 Callerapi through Composio's Tool Router. The agent can perform Callerapi 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 Callerapi MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/callerapi/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/callerapi/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/callerapi/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/callerapi/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/callerapi/framework/codex) - [OpenClaw](https://composio.dev/toolkits/callerapi/framework/openclaw) - [Hermes](https://composio.dev/toolkits/callerapi/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/callerapi/framework/cli) - [Google ADK](https://composio.dev/toolkits/callerapi/framework/google-adk) - [LangChain](https://composio.dev/toolkits/callerapi/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/callerapi/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/callerapi/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/callerapi/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. It helps businesses automate support and streamline interactions through natural, voice-powered conversations. - [Botsonic](https://composio.dev/toolkits/botsonic) - Botsonic is a no-code AI chatbot builder for easily creating and deploying chatbots to your website. It empowers businesses to offer conversational experiences without writing code. - [Botstar](https://composio.dev/toolkits/botstar) - BotStar is a comprehensive chatbot platform for designing, developing, and training chatbots visually on Messenger and websites. It helps businesses automate conversations and customer interactions without coding. - [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. It streamlines client work and saves you serious admin time. - [Convolo ai](https://composio.dev/toolkits/convolo_ai) - Convolo ai is an AI-powered communications platform for sales teams. It accelerates lead response and improves conversion rates by automating calls and integrating workflows. - [Delighted](https://composio.dev/toolkits/delighted) - Delighted is a customer feedback platform based on the Net Promoter System®. It helps you quickly gather, track, and act on customer sentiment. - [Docsbot ai](https://composio.dev/toolkits/docsbot_ai) - Docsbot ai is a platform that lets you build custom AI chatbots trained on your documentation. It automates customer support and content generation, saving time and improving response quality. - [Emelia](https://composio.dev/toolkits/emelia) - Emelia is an all-in-one B2B prospecting platform for cold-email, LinkedIn outreach, and prospect research. It streamlines outbound campaigns so you can find, engage, and warm up leads faster. - [Findymail](https://composio.dev/toolkits/findymail) - Findymail is a B2B data provider offering verified email and phone contacts for sales prospecting. 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 Callerapi MCP? With a standalone Callerapi MCP server, the agents and LLMs can only access a fixed set of Callerapi tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Callerapi 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 Callerapi tools. ### Can I manage the permissions and scopes for Callerapi while using Tool Router? Yes, absolutely. You can configure which Callerapi 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 Callerapi data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)