# How to integrate Linkly MCP with Pydantic AI ```json { "title": "How to integrate Linkly MCP with Pydantic AI", "toolkit": "Linkly", "toolkit_slug": "linkly", "framework": "Pydantic AI", "framework_slug": "pydantic-ai", "url": "https://composio.dev/toolkits/linkly/framework/pydantic-ai", "markdown_url": "https://composio.dev/toolkits/linkly/framework/pydantic-ai.md", "updated_at": "2026-03-29T06:40:37.907Z" } ``` ## Introduction This guide walks you through connecting Linkly to Pydantic AI using the Composio tool router. By the end, you'll have a working Linkly agent that can create a tracking link for new product, list all active tracking links, add a retargeting tag to a link through natural language commands. This guide will help you understand how to give your Pydantic AI agent real control over a Linkly account through Composio's Linkly MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Linkly with - [OpenAI Agents SDK](https://composio.dev/toolkits/linkly/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/linkly/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/linkly/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/linkly/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/linkly/framework/codex) - [OpenClaw](https://composio.dev/toolkits/linkly/framework/openclaw) - [Hermes](https://composio.dev/toolkits/linkly/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/linkly/framework/cli) - [Google ADK](https://composio.dev/toolkits/linkly/framework/google-adk) - [LangChain](https://composio.dev/toolkits/linkly/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/linkly/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/linkly/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/linkly/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/linkly/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 Linkly - 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 Linkly 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 Linkly MCP server, and what's possible with it? The Linkly MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Linkly account. It provides structured and secure access so your agent can perform Linkly operations on your behalf. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `LINKLY_CREATE_OR_UPDATE_LINK` | Create or Update Link | Tool to create a new shortened link or update an existing one in Linkly. Use when you need to generate a trackable short URL with custom parameters, UTM tracking, retargeting pixels, or Open Graph metadata. To create a new link, provide url and workspace_id. To update an existing link, provide id and the fields you want to change. | | `LINKLY_DELETE_LINK` | Delete Link | Tool to delete a specific link by ID from a workspace. Use when you need to permanently remove a link. This action is permanent and cannot be undone. | | `LINKLY_DELETE_LINKS` | Delete Links | Tool to delete one or more links by their IDs. This action is permanent and cannot be undone. Use when you need to remove links from a workspace. | | `LINKLY_EXPORT_LINKS` | Export Links | Tool to export all links in a workspace as JSON or CSV. Use when you need to retrieve all links for backup, analysis, or migration purposes. | | `LINKLY_GET_CLICK_COUNTERS_BY_DIMENSION` | Get Click Counters by Dimension | Tool to retrieve click analytics grouped by a specific dimension (counter). Returns aggregated counts for each unique value of the selected dimension. Use when you need to analyze click patterns by country, platform, browser, referrer, ISP, link, or URL parameters. | | `LINKLY_GET_CLICK_ANALYTICS` | Get Click Analytics | Tool to retrieve click analytics for a workspace. Filter by link, date range, country, and more. Returns time-series data suitable for charting. | | `LINKLY_GET_LINK_DETAILS` | Get Link Details | Tool to retrieve detailed information about a specific link by its ID. Use when you need to fetch link configuration, UTM parameters, or click statistics. | | `LINKLY_GET_LINK_BY_ID` | Get Link By ID | Tool to retrieve details for a specific link by ID. Use when you need to fetch information about a shortened link, including its destination URL, click statistics, and configuration settings. | | `LINKLY_LIST_DOMAINS` | List Domains | Tool to retrieve all custom domains configured for a workspace. Use when you need to see available domains for creating short links. | | `LINKLY_LIST_LINKS` | List Links | Tool to get a paginated list of all links in a workspace. Supports search, sorting, and pagination. Returns link details including click statistics. Use when you need to retrieve or search through links. | | `LINKLY_LIST_LINK_WEBHOOKS` | List Link Webhooks | Tool to retrieve all webhook subscriptions for a specific link. Use when you need to see what webhooks are configured for a link. | | `LINKLY_LIST_WORKSPACES` | List Workspaces | Tool to retrieve all workspaces the authenticated user has access to. Use this to discover available workspace IDs for other API calls. | | `LINKLY_LIST_WORKSPACE_WEBHOOKS` | List workspace webhooks | Tool to list all webhook subscriptions for a specific workspace. Use when you need to retrieve or view the configured webhooks for a workspace. | | `LINKLY_SUBSCRIBE_WEBHOOK_TO_LINK` | Subscribe webhook to link | Tool to subscribe a webhook URL to receive notifications when a specific link is clicked. Use when you need to track click events for a shortened link. | | `LINKLY_SUBSCRIBE_WEBHOOK_TO_WORKSPACE` | Subscribe Webhook to Workspace | Tool to subscribe a webhook URL to receive click notifications from a Linkly workspace. Use when you need to set up real-time notifications for link clicks. The webhook will receive POST requests containing click data including country, platform, browser, and other analytics information whenever any link in the workspace is clicked. | | `LINKLY_UNSUBSCRIBE_WEBHOOK_FROM_LINK` | Unsubscribe Webhook from Link | Tool to remove a webhook subscription from a link. Use when you need to stop receiving webhook events for a specific link. | | `LINKLY_UNSUBSCRIBE_WEBHOOK_FROM_WORKSPACE` | Unsubscribe Webhook From Workspace | Tool to remove a webhook subscription from a workspace. Use when you need to unsubscribe a webhook URL from receiving events for a specific workspace. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Linkly MCP server is an implementation of the Model Context Protocol that connects your AI agent to Linkly. It provides structured and secure access so your agent can perform Linkly 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 Linkly - 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 Linkly - MCPServerStreamableHTTP connects to the Linkly 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 Linkly 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 Linkly composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["linkly"], ) 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 Linkly endpoint - The agent uses GPT-5 to interpret user commands and perform Linkly operations - The instructions field defines the agent's role and behavior ```python # Attach the MCP server to a Pydantic AI Agent linkly_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[linkly_mcp], instructions=( "You are a Linkly assistant. Use Linkly 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 - Linkly 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 Linkly.\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 Linkly composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["linkly"], ) 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 linkly_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[linkly_mcp], instructions=( "You are a Linkly assistant. Use Linkly 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 Linkly.\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 Linkly through Composio's Tool Router. With this setup, your agent can perform real Linkly 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 + Linkly 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 Linkly MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/linkly/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/linkly/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/linkly/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/linkly/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/linkly/framework/codex) - [OpenClaw](https://composio.dev/toolkits/linkly/framework/openclaw) - [Hermes](https://composio.dev/toolkits/linkly/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/linkly/framework/cli) - [Google ADK](https://composio.dev/toolkits/linkly/framework/google-adk) - [LangChain](https://composio.dev/toolkits/linkly/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/linkly/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/linkly/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/linkly/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/linkly/framework/crew-ai) ## Related Toolkits - [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. - [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. - [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. - [ActiveTrail](https://composio.dev/toolkits/active_trail) - ActiveTrail is a user-friendly email marketing and automation platform. It helps you reach subscribers and automate campaigns with ease. - [Ahrefs](https://composio.dev/toolkits/ahrefs) - Ahrefs is an SEO and marketing platform for site audits, keyword research, and competitor insights. It helps you improve search rankings and drive organic traffic. - [Amcards](https://composio.dev/toolkits/amcards) - AMCards lets you create and mail personalized greeting cards online. Build stronger customer relationships with easy, automated card campaigns. - [Beamer](https://composio.dev/toolkits/beamer) - Beamer is a news and changelog platform for in-app announcements and feature updates. It helps companies boost user engagement by sharing news where users are most active. - [Benchmark email](https://composio.dev/toolkits/benchmark_email) - Benchmark Email is a platform for creating, sending, and tracking email campaigns. It's built to help you engage audiences and analyze results—all in one place. - [Bigmailer](https://composio.dev/toolkits/bigmailer) - BigMailer is an email marketing platform for managing multiple brands with white-labeling and automation. It helps teams streamline campaigns and simplify integration with Amazon SES. - [Brandfetch](https://composio.dev/toolkits/brandfetch) - Brandfetch is an API that delivers company logos, colors, and visual branding assets. It helps marketers and developers keep brand visuals consistent everywhere. - [Brevo](https://composio.dev/toolkits/brevo) - Brevo is an all-in-one email and SMS marketing platform for transactional messaging, automation, and CRM. It helps businesses engage customers and streamline communications through powerful campaign tools. - [Campayn](https://composio.dev/toolkits/campayn) - Campayn is an email marketing platform for creating, sending, and managing campaigns. It helps businesses engage contacts and grow audiences with easy-to-use tools. - [Cardly](https://composio.dev/toolkits/cardly) - Cardly is a platform for creating and sending personalized direct mail to customers. It helps businesses break through the digital clutter by getting real engagement via physical mailboxes. - [ClickSend](https://composio.dev/toolkits/clicksend) - ClickSend is a cloud-based SMS and email marketing platform for businesses. It streamlines communication by enabling quick message delivery and contact management. - [Crustdata](https://composio.dev/toolkits/crustdata) - CrustData is an AI-powered data intelligence platform for real-time company and people data. It helps B2B sales teams, AI SDRs, and investors react to live business signals. - [Curated](https://composio.dev/toolkits/curated) - Curated is a platform for collecting, curating, and publishing newsletters. It streamlines content aggregation and distribution for creators and teams. - [Customerio](https://composio.dev/toolkits/customerio) - Customer.io is a customer engagement platform for targeted messaging across email, SMS, and push. Easily automate, segment, and track communications with your audience. - [Cutt ly](https://composio.dev/toolkits/cutt_ly) - Cutt.ly is a URL shortening service for managing and analyzing links. Streamline your workflows with quick, trackable, and branded short URLs. - [Demio](https://composio.dev/toolkits/demio) - Demio is webinar software built for marketers, offering both live and automated sessions with interactive features. It helps teams engage audiences and optimize lead generation through detailed analytics. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Linkly MCP? With a standalone Linkly MCP server, the agents and LLMs can only access a fixed set of Linkly tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Linkly 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 Linkly tools. ### Can I manage the permissions and scopes for Linkly while using Tool Router? Yes, absolutely. You can configure which Linkly 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 Linkly data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)