# How to integrate Dub MCP with CrewAI ```json { "title": "How to integrate Dub MCP with CrewAI", "toolkit": "Dub", "toolkit_slug": "dub", "framework": "CrewAI", "framework_slug": "crew-ai", "url": "https://composio.dev/toolkits/dub/framework/crew-ai", "markdown_url": "https://composio.dev/toolkits/dub/framework/crew-ai.md", "updated_at": "2026-03-29T06:31:40.325Z" } ``` ## Introduction This guide walks you through connecting Dub to CrewAI using the Composio tool router. By the end, you'll have a working Dub agent that can create a branded short link for event registration, show analytics for "newsletter" short link, update destination url for your sales link through natural language commands. This guide will help you understand how to give your CrewAI agent real control over a Dub account through Composio's Dub MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Dub with - [OpenAI Agents SDK](https://composio.dev/toolkits/dub/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/dub/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/dub/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/dub/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/dub/framework/codex) - [OpenClaw](https://composio.dev/toolkits/dub/framework/openclaw) - [Hermes](https://composio.dev/toolkits/dub/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/dub/framework/cli) - [Google ADK](https://composio.dev/toolkits/dub/framework/google-adk) - [LangChain](https://composio.dev/toolkits/dub/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/dub/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/dub/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/dub/framework/llama-index) ## TL;DR Here's what you'll learn: - Get a Composio API key and configure your Dub connection - Set up CrewAI with an MCP enabled agent - Create a Tool Router session or standalone MCP server for Dub - Build a conversational loop where your agent can execute Dub 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 Dub MCP server, and what's possible with it? The Dub MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Dub account. It provides structured and secure access so your agent can perform Dub operations on your behalf. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `DUB_BULK_DELETE_LINKS` | Bulk Delete Links | Tool to delete multiple short links in bulk from Dub. Use when you need to remove multiple links at once. Maximum of 100 link IDs per request. Non-existing IDs are silently ignored. | | `DUB_BULK_UPDATE_LINKS` | Bulk Update Links | Tool to update multiple short links in bulk. Use when you need to apply the same updates to multiple links at once by specifying link IDs or external IDs. | | `DUB_CREATE_DOMAIN` | Create Domain | Tool to add a domain to a Dub workspace. Use when you need to create a new domain for shortening links. The domain must be verified before it can be used for link shortening. | | `DUB_CREATE_TAG` | Create Tag | Tool to create a new tag in Dub. Use when you need to organize links by creating custom tags. Tags help categorize and filter links for better organization. | | `DUB_DELETE_DOMAIN` | Delete Domain | Tool to delete a domain from your Dub workspace. Use when you need to permanently remove a domain. The domain must exist and be owned by your workspace. | | `DUB_DELETE_TAG` | Delete Tag | Tool to delete a tag from Dub. Use when you need to remove a tag that is no longer needed. | | `DUB_GET_LINK_INFO` | Get Link Info | Tool to retrieve details of a specific short link from Dub. Use when you need to get comprehensive information about a link including its configuration, targeting settings, and performance metrics. | | `DUB_GET_LINKS` | Get Links | Tool to retrieve a paginated list of links for the authenticated workspace. Use when you need to list links with optional filtering by domain, tags, folder, search terms, or user. Supports pagination and sorting for efficient retrieval of large link collections. | | `DUB_GET_LINKS_COUNT` | Get Links Count | Tool to retrieve the count of links in workspace with optional filters. Use when you need to get the total number of links matching specific criteria such as domain, tags, folder, or search terms. | | `DUB_RETRIEVE_LIST_OF_TAGS` | Retrieve List of Tags | Tool to retrieve a list of tags from Dub. Use when you need to fetch all tags or search for specific tags by name or IDs. Supports pagination and sorting by name or creation date. | | `DUB_GET_WORKSPACE` | Get Workspace | Tool to retrieve detailed information for a specific workspace. Use when you need to get workspace details including plan, usage limits, domains, users, and configuration settings. | | `DUB_LIST_DOMAINS` | List Domains | Tool to retrieve a list of domains for the authenticated workspace. Use when you need to view all domains, search for specific domains, or filter domains by archived status. Supports pagination for large result sets. | | `DUB_TRACK_DEEP_LINK_OPEN_EVENT` | Track Deep Link Open Event | Tool to track a deep link open event in Dub. Use when you need to record when a user opens your app via a deep link. Supports both direct tracking via deepLink parameter or probabilistic tracking via dubDomain parameter. | | `DUB_UPDATE_DOMAIN` | Update Domain | Tool to update a domain configuration in Dub. Use when you need to modify domain settings like redirect URLs, placeholder text, archive status, or deep linking configurations. | | `DUB_UPDATE_TAG` | Update Tag | Tool to update an existing tag by ID. Use when you need to change the name or color of a tag. | | `DUB_UPDATE_WORKSPACE` | Update Workspace | Tool to update workspace settings in Dub. Use when you need to modify workspace name, slug, logo, or conversion tracking settings. | | `DUB_UPSERT_A_LINK` | Upsert a Link | Tool to create or update a short link in Dub. Use when you need to create a new short link or update an existing one. If the link already exists (matching domain and key), it will be updated; otherwise, a new link will be created. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Dub MCP server is an implementation of the Model Context Protocol that connects your AI agent to Dub. It provides structured and secure access so your agent can perform Dub 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 Dub 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 Dub 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 Dub 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 Dub **What's happening:** - You create a Dub only session through Composio - Composio returns an MCP HTTP URL that exposes Dub tools ```python composio_client = Composio(api_key=COMPOSIO_API_KEY) session = composio_client.create(user_id=COMPOSIO_USER_ID, toolkits=["dub"]) 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=["dub"], ) 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 Dub through Composio's Tool Router. The agent can perform Dub 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 Dub MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/dub/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/dub/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/dub/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/dub/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/dub/framework/codex) - [OpenClaw](https://composio.dev/toolkits/dub/framework/openclaw) - [Hermes](https://composio.dev/toolkits/dub/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/dub/framework/cli) - [Google ADK](https://composio.dev/toolkits/dub/framework/google-adk) - [LangChain](https://composio.dev/toolkits/dub/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/dub/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/dub/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/dub/framework/llama-index) ## Related Toolkits - [Google Sheets](https://composio.dev/toolkits/googlesheets) - Google Sheets is a cloud-based spreadsheet tool for real-time collaboration and data analysis. It lets teams work together from anywhere, updating information instantly. - [Notion](https://composio.dev/toolkits/notion) - Notion is a collaborative workspace for notes, docs, wikis, and tasks. It streamlines team knowledge, project tracking, and workflow customization in one place. - [Airtable](https://composio.dev/toolkits/airtable) - Airtable combines the flexibility of spreadsheets with the power of a database for easy project and data management. Teams use Airtable to organize, track, and collaborate with custom views and automations. - [Asana](https://composio.dev/toolkits/asana) - Asana is a collaborative work management platform for teams to organize and track projects. It streamlines teamwork, boosts productivity, and keeps everyone aligned on goals. - [Google Tasks](https://composio.dev/toolkits/googletasks) - Google Tasks is a to-do list and task management tool integrated into Gmail and Google Calendar. It helps you organize, track, and complete tasks across your Google ecosystem. - [Linear](https://composio.dev/toolkits/linear) - Linear is a modern issue tracking and project planning tool for fast-moving teams. It helps streamline workflows, organize projects, and boost productivity. - [Firecrawl](https://composio.dev/toolkits/firecrawl) - Firecrawl automates large-scale web crawling and data extraction. It helps organizations efficiently gather, index, and analyze content from online sources. - [Tavily](https://composio.dev/toolkits/tavily) - Tavily offers powerful search and data retrieval from documents, databases, and the web. It helps teams locate and filter information instantly, saving hours on research. - [Jira](https://composio.dev/toolkits/jira) - Jira is Atlassian’s platform for bug tracking, issue tracking, and agile project management. It helps teams organize work, prioritize tasks, and deliver projects efficiently. - [Exa](https://composio.dev/toolkits/exa) - Exa is a data extraction and search platform for gathering and analyzing information from websites, APIs, or databases. It helps teams quickly surface insights and automate data-driven workflows. - [Serpapi](https://composio.dev/toolkits/serpapi) - SerpApi is a real-time API for structured search engine results. It lets you automate SERP data collection, parsing, and analysis for SEO and research. - [Clickup](https://composio.dev/toolkits/clickup) - ClickUp is an all-in-one productivity platform for managing tasks, docs, goals, and team collaboration. It streamlines project workflows so teams can work smarter and stay organized in one place. - [Monday](https://composio.dev/toolkits/monday) - Monday.com is a customizable work management platform for project planning and collaboration. It helps teams organize tasks, automate workflows, and track progress in real time. - [Reddit](https://composio.dev/toolkits/reddit) - Reddit is a social news platform with thriving user-driven communities (subreddits). It's the go-to place for discussion, content sharing, and viral marketing. - [Peopledatalabs](https://composio.dev/toolkits/peopledatalabs) - Peopledatalabs delivers B2B data enrichment and identity resolution APIs. Supercharge your apps with accurate, up-to-date business and contact data. - [Snowflake](https://composio.dev/toolkits/snowflake) - Snowflake is a cloud data warehouse built for elastic scaling, secure data sharing, and fast SQL analytics across major clouds. - [Facebook](https://composio.dev/toolkits/facebook) - Facebook is a social media and advertising platform for businesses and creators. It helps you connect, share, and manage content across your public Facebook Pages. - [Posthog](https://composio.dev/toolkits/posthog) - PostHog is an open-source analytics platform for tracking user interactions and product metrics. It helps teams refine features, analyze funnels, and reduce churn with actionable insights. - [Linkedin](https://composio.dev/toolkits/linkedin) - LinkedIn is a professional networking platform for connecting, sharing content, and engaging with business opportunities. It's the go-to place for building your professional brand and unlocking new career connections. - [Active campaign](https://composio.dev/toolkits/active_campaign) - ActiveCampaign is a marketing automation and CRM platform for managing email campaigns, sales pipelines, and customer segmentation. It helps businesses engage customers and drive growth through smart automation and targeted outreach. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Dub MCP? With a standalone Dub MCP server, the agents and LLMs can only access a fixed set of Dub tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Dub 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 Dub tools. ### Can I manage the permissions and scopes for Dub while using Tool Router? Yes, absolutely. You can configure which Dub 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 Dub data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)