# How to integrate Dub MCP with Pydantic AI ```json { "title": "How to integrate Dub MCP with Pydantic AI", "toolkit": "Dub", "toolkit_slug": "dub", "framework": "Pydantic AI", "framework_slug": "pydantic-ai", "url": "https://composio.dev/toolkits/dub/framework/pydantic-ai", "markdown_url": "https://composio.dev/toolkits/dub/framework/pydantic-ai.md", "updated_at": "2026-03-29T06:31:40.325Z" } ``` ## Introduction This guide walks you through connecting Dub to Pydantic AI 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 Pydantic AI 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) - [CrewAI](https://composio.dev/toolkits/dub/framework/crew-ai) ## TL;DR Here's what you'll learn: - How to set up your Composio API key and User ID - How to create a Composio Tool Router session for Dub - How to attach an MCP Server to a Pydantic AI agent - How to stream responses and maintain chat history - How to build a simple REPL-style chat interface to test your Dub workflows ## What is Pydantic AI? Pydantic AI is a Python framework for building AI agents with strong typing and validation. It leverages Pydantic's data validation capabilities to create robust, type-safe AI applications. Key features include: - Type Safety: Built on Pydantic for automatic data validation - MCP Support: Native support for Model Context Protocol servers - Streaming: Built-in support for streaming responses - Async First: Designed for async/await patterns ## 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 with an active API key - Basic familiarity with Python and async programming ### 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 Install the required libraries. What's happening: - composio connects your agent to external SaaS tools like Dub - pydantic-ai lets you create structured AI agents with tool support - python-dotenv loads your environment variables securely from a .env file ```bash pip install composio pydantic-ai python-dotenv ``` ### 3. Set up environment variables Create a .env file in your project root. What's happening: - COMPOSIO_API_KEY authenticates your agent to Composio's API - USER_ID associates your session with your account for secure tool access - OPENAI_API_KEY to access OpenAI LLMs ```bash COMPOSIO_API_KEY=your_composio_api_key_here USER_ID=your_user_id_here OPENAI_API_KEY=your_openai_api_key ``` ### 4. Import dependencies What's happening: - We load environment variables and import required modules - Composio manages connections to Dub - MCPServerStreamableHTTP connects to the Dub MCP server endpoint - Agent from Pydantic AI lets you define and run the AI assistant ```python import asyncio import os from dotenv import load_dotenv from composio import Composio from pydantic_ai import Agent from pydantic_ai.mcp import MCPServerStreamableHTTP load_dotenv() ``` ### 5. Create a Tool Router Session What's happening: - We're creating a Tool Router session that gives your agent access to Dub tools - The create method takes the user ID and specifies which toolkits should be available - The returned session.mcp.url is the MCP server URL that your agent will use ```python async def main(): api_key = os.getenv("COMPOSIO_API_KEY") user_id = os.getenv("USER_ID") if not api_key or not user_id: raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment") # Create a Composio Tool Router session for Dub composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["dub"], ) url = session.mcp.url if not url: raise ValueError("Composio session did not return an MCP URL") ``` ### 6. Initialize the Pydantic AI Agent What's happening: - The MCP client connects to the Dub endpoint - The agent uses GPT-5 to interpret user commands and perform Dub operations - The instructions field defines the agent's role and behavior ```python # Attach the MCP server to a Pydantic AI Agent dub_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[dub_mcp], instructions=( "You are a Dub assistant. Use Dub tools to help users " "with their requests. Ask clarifying questions when needed." ), ) ``` ### 7. Build the chat interface What's happening: - The agent reads input from the terminal and streams its response - Dub API calls happen automatically under the hood - The model keeps conversation history to maintain context across turns ```python # Simple REPL with message history history = [] print("Chat started! Type 'exit' or 'quit' to end.\n") print("Try asking the agent to help you with Dub.\n") while True: user_input = input("You: ").strip() if user_input.lower() in {"exit", "quit", "bye"}: print("\nGoodbye!") break if not user_input: continue print("\nAgent is thinking...\n", flush=True) async with agent.run_stream(user_input, message_history=history) as stream_result: collected_text = "" async for chunk in stream_result.stream_output(): text_piece = None if isinstance(chunk, str): text_piece = chunk elif hasattr(chunk, "delta") and isinstance(chunk.delta, str): text_piece = chunk.delta elif hasattr(chunk, "text"): text_piece = chunk.text if text_piece: collected_text += text_piece result = stream_result print(f"Agent: {collected_text}\n") history = result.all_messages() ``` ### 8. Run the application What's happening: - The asyncio loop launches the agent and keeps it running until you exit ```python if __name__ == "__main__": asyncio.run(main()) ``` ## Complete Code ```python import asyncio import os from dotenv import load_dotenv from composio import Composio from pydantic_ai import Agent from pydantic_ai.mcp import MCPServerStreamableHTTP load_dotenv() async def main(): api_key = os.getenv("COMPOSIO_API_KEY") user_id = os.getenv("USER_ID") if not api_key or not user_id: raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment") # Create a Composio Tool Router session for Dub composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["dub"], ) url = session.mcp.url if not url: raise ValueError("Composio session did not return an MCP URL") # Attach the MCP server to a Pydantic AI Agent dub_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[dub_mcp], instructions=( "You are a Dub assistant. Use Dub tools to help users " "with their requests. Ask clarifying questions when needed." ), ) # Simple REPL with message history history = [] print("Chat started! Type 'exit' or 'quit' to end.\n") print("Try asking the agent to help you with Dub.\n") while True: user_input = input("You: ").strip() if user_input.lower() in {"exit", "quit", "bye"}: print("\nGoodbye!") break if not user_input: continue print("\nAgent is thinking...\n", flush=True) async with agent.run_stream(user_input, message_history=history) as stream_result: collected_text = "" async for chunk in stream_result.stream_output(): text_piece = None if isinstance(chunk, str): text_piece = chunk elif hasattr(chunk, "delta") and isinstance(chunk.delta, str): text_piece = chunk.delta elif hasattr(chunk, "text"): text_piece = chunk.text if text_piece: collected_text += text_piece result = stream_result print(f"Agent: {collected_text}\n") history = result.all_messages() if __name__ == "__main__": asyncio.run(main()) ``` ## Conclusion You've built a Pydantic AI agent that can interact with Dub through Composio's Tool Router. With this setup, your agent can perform real Dub actions through natural language. You can extend this further by: - Adding other toolkits like Gmail, HubSpot, or Salesforce - Building a web-based chat interface around this agent - Using multiple MCP endpoints to enable cross-app workflows (for example, Gmail + Dub for workflow automation) This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations. ## 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) - [CrewAI](https://composio.dev/toolkits/dub/framework/crew-ai) ## 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 Pydantic AI? Yes, you can. Pydantic AI 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)