# How to integrate Altoviz MCP with CrewAI ```json { "title": "How to integrate Altoviz MCP with CrewAI", "toolkit": "Altoviz", "toolkit_slug": "altoviz", "framework": "CrewAI", "framework_slug": "crew-ai", "url": "https://composio.dev/toolkits/altoviz/framework/crew-ai", "markdown_url": "https://composio.dev/toolkits/altoviz/framework/crew-ai.md", "updated_at": "2026-05-06T08:00:13.619Z" } ``` ## Introduction This guide walks you through connecting Altoviz to CrewAI using the Composio tool router. By the end, you'll have a working Altoviz agent that can find customer details by email address, update a client's company information, retrieve current vat rates for invoices through natural language commands. This guide will help you understand how to give your CrewAI agent real control over a Altoviz account through Composio's Altoviz MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Altoviz with - [OpenAI Agents SDK](https://composio.dev/toolkits/altoviz/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/altoviz/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/altoviz/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/altoviz/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/altoviz/framework/codex) - [OpenClaw](https://composio.dev/toolkits/altoviz/framework/openclaw) - [Hermes](https://composio.dev/toolkits/altoviz/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/altoviz/framework/cli) - [Google ADK](https://composio.dev/toolkits/altoviz/framework/google-adk) - [LangChain](https://composio.dev/toolkits/altoviz/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/altoviz/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/altoviz/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/altoviz/framework/llama-index) ## TL;DR Here's what you'll learn: - Get a Composio API key and configure your Altoviz connection - Set up CrewAI with an MCP enabled agent - Create a Tool Router session or standalone MCP server for Altoviz - Build a conversational loop where your agent can execute Altoviz 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 Altoviz MCP server, and what's possible with it? The Altoviz MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Altoviz account. It provides structured and secure access to your billing, invoicing, and customer management data, so your agent can manage products, find customers, update records, and retrieve financial information on your behalf. - Product management and creation: Instruct your agent to create new products, update details, or delete products from your Altoviz catalog with ease. - Customer and contact lookup: Effortlessly find customers or contacts by email, enabling quick access to client details and supporting streamlined communication. - Financial classification and VAT management: Let your agent fetch available classifications and VAT rates, ensuring accurate tax handling and financial document setup. - Unit retrieval for transactions: Retrieve all available measurement units in your system, supporting precise product and invoice management. - Customer information updates: Have your agent modify or update customer records, keeping your business data up-to-date without manual intervention. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `ALTOVIZ_CREATE_PRODUCT` | Create Product | Creates a new product in the altoviz system. this tool allows for the independent creation of a product with all necessary details. | | `ALTOVIZ_DELETE_PRODUCT` | Delete Product | This tool allows you to delete an existing product from altoviz. the action permanently removes the product from the system. | | `ALTOVIZ_FIND_CONTACT` | Find Contact by Email | This tool allows searching for contacts in altoviz using an email address. the action is independently executable and returns contact details if found. | | `ALTOVIZ_FIND_CUSTOMER` | Find Customer by Email | This tool allows you to find a customer in altoviz by their email address. this is a standalone action that doesn't require any resource ids or dependencies on other tools. | | `ALTOVIZ_FIND_PRODUCT` | Find Product by Number | This tool allows users to find products in altoviz using the product number. it retrieves detailed product information including id, name, number, description, price, and other relevant metadata. it is a critical operation for product management in altoviz. | | `ALTOVIZ_GET_CLASSIFICATIONS` | Get Classifications List | This tool retrieves a list of classifications from the altoviz platform. classifications are essential for producing accounting registers from user-created invoices. it can fetch all classifications or filter them by type. | | `ALTOVIZ_GET_UNITS` | Get Units List | This tool retrieves a list of all available units in the altoviz system. units are used for product measurements and quantity specifications in various transactions. | | `ALTOVIZ_GET_VATS` | Get VAT Rates | This tool retrieves a list of all available vat rates from altoviz. it's essential for creating and managing invoices and quotes where vat calculations are required. it supports retrieving vat rates, validating them for different regions, and ensuring correct tax calculations in financial documents. | | `ALTOVIZ_UPDATE_CUSTOMER` | Update Customer Information | This tool updates an existing customer's information in altoviz. it enables modification of various customer details including contact information, company details, and personal information. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Altoviz MCP server is an implementation of the Model Context Protocol that connects your AI agent to Altoviz. It provides structured and secure access so your agent can perform Altoviz 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 Altoviz 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 Altoviz 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 Altoviz 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 Altoviz **What's happening:** - You create a Altoviz only session through Composio - Composio returns an MCP HTTP URL that exposes Altoviz tools ```python composio_client = Composio(api_key=COMPOSIO_API_KEY) session = composio_client.create(user_id=COMPOSIO_USER_ID, toolkits=["altoviz"]) 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=["altoviz"], ) 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 Altoviz through Composio's Tool Router. The agent can perform Altoviz 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 Altoviz MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/altoviz/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/altoviz/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/altoviz/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/altoviz/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/altoviz/framework/codex) - [OpenClaw](https://composio.dev/toolkits/altoviz/framework/openclaw) - [Hermes](https://composio.dev/toolkits/altoviz/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/altoviz/framework/cli) - [Google ADK](https://composio.dev/toolkits/altoviz/framework/google-adk) - [LangChain](https://composio.dev/toolkits/altoviz/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/altoviz/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/altoviz/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/altoviz/framework/llama-index) ## Related Toolkits - [Stripe](https://composio.dev/toolkits/stripe) - Stripe is a global online payments platform offering APIs for managing payments, customers, and subscriptions. Trusted by businesses for secure, efficient, and scalable payment processing worldwide. - [Alpha vantage](https://composio.dev/toolkits/alpha_vantage) - Alpha Vantage is a financial data platform offering real-time and historical stock market APIs. Get instant, reliable access to equities, forex, and technical analysis data for smarter trading decisions. - [Benzinga](https://composio.dev/toolkits/benzinga) - Benzinga provides real-time financial news and data APIs for market coverage. It helps you track breaking news and actionable market insights instantly. - [Brex](https://composio.dev/toolkits/brex) - Brex provides corporate credit cards and spend management tailored for startups and tech businesses. It helps optimize company cash flow, streamline accounting, and accelerate business growth. - [Chaser](https://composio.dev/toolkits/chaser) - Chaser is accounts receivable automation software that sends invoice reminders and helps businesses get paid faster. It streamlines the collections process to save time and improve cash flow. - [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. - [Coinbase](https://composio.dev/toolkits/coinbase) - Coinbase is a platform for buying, selling, and storing cryptocurrency. It makes exchanging and managing crypto simple and secure for everyone. - [Coinranking](https://composio.dev/toolkits/coinranking) - Coinranking is a comprehensive cryptocurrency market data platform offering access to real-time coin prices, market caps, and historical data. Get accurate, up-to-date stats for thousands of digital assets in one place. - [Coupa](https://composio.dev/toolkits/coupa) - Coupa is a business spend management platform for procurement, invoicing, and expenses. It helps organizations streamline purchasing, control costs, and gain complete visibility over financial operations. - [CurrencyScoop](https://composio.dev/toolkits/currencyscoop) - CurrencyScoop is a developer-friendly API for real-time and historical currency exchange rates. Easily access fiat and crypto data for smart, up-to-date financial applications. - [Daffy](https://composio.dev/toolkits/daffy) - Daffy is a modern charitable giving platform with a donor-advised fund. Easily set aside funds, grow them tax-free, and donate to over 1.7 million U.S. charities. - [Eagle doc](https://composio.dev/toolkits/eagle_doc) - Eagle doc is an AI-powered OCR API for invoices and receipts. It delivers fast, reliable, and accurate document data extraction for seamless automation. - [Elorus](https://composio.dev/toolkits/elorus) - Elorus is an online invoicing and time-tracking software for freelancers and small businesses. Easily manage finances, bill clients, and track work in one place. - [Eodhd apis](https://composio.dev/toolkits/eodhd_apis) - Eodhd apis delivers comprehensive financial data, including live and historical stock prices, via robust APIs. Easily access reliable, up-to-date market insights to power your apps, dashboards, and analytics. - [Fidel api](https://composio.dev/toolkits/fidel_api) - Fidel api is a secure platform for linking payment cards to web and mobile apps. It enables real-time card transaction monitoring and event-based automation for businesses. - [Finage](https://composio.dev/toolkits/finage) - Finage is a secure API platform delivering real-time and historical financial data for stocks, forex, crypto, indices, and commodities. It empowers developers and businesses to access, analyze, and act on market data instantly. - [Finmei](https://composio.dev/toolkits/finmei) - Finmei is an invoicing tool that simplifies billing, invoice management, and expense tracking. Ideal for automating and organizing your business finances in one place. - [Fixer](https://composio.dev/toolkits/fixer) - Fixer is a currency data API offering real-time and historical exchange rates for 170 currencies. Instantly access accurate, up-to-date forex data for your applications and workflows. - [Fixer io](https://composio.dev/toolkits/fixer_io) - Fixer.io is a lightweight API for real-time and historical foreign exchange rates. It makes global currency conversion fast, accurate, and hassle-free. - [Flutterwave](https://composio.dev/toolkits/flutterwave) - Flutterwave is a global payments platform enabling businesses to accept and send payments across Africa and beyond. Its robust APIs simplify cross-border transactions and financial operations. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Altoviz MCP? With a standalone Altoviz MCP server, the agents and LLMs can only access a fixed set of Altoviz tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Altoviz 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 Altoviz tools. ### Can I manage the permissions and scopes for Altoviz while using Tool Router? Yes, absolutely. You can configure which Altoviz 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 Altoviz data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) ยท [Composio docs](https://docs.composio.dev/llms.txt)