# How to integrate Sendloop MCP with Pydantic AI ```json { "title": "How to integrate Sendloop MCP with Pydantic AI", "toolkit": "Sendloop", "toolkit_slug": "sendloop", "framework": "Pydantic AI", "framework_slug": "pydantic-ai", "url": "https://composio.dev/toolkits/sendloop/framework/pydantic-ai", "markdown_url": "https://composio.dev/toolkits/sendloop/framework/pydantic-ai.md", "updated_at": "2026-05-06T08:27:39.298Z" } ``` ## Introduction This guide walks you through connecting Sendloop to Pydantic AI using the Composio tool router. By the end, you'll have a working Sendloop agent that can show open and scheduled campaigns this week, list all subscribers in your main list, get summary report for last email blast through natural language commands. This guide will help you understand how to give your Pydantic AI agent real control over a Sendloop account through Composio's Sendloop MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Sendloop with - [OpenAI Agents SDK](https://composio.dev/toolkits/sendloop/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/sendloop/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/sendloop/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/sendloop/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/sendloop/framework/codex) - [OpenClaw](https://composio.dev/toolkits/sendloop/framework/openclaw) - [Hermes](https://composio.dev/toolkits/sendloop/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/sendloop/framework/cli) - [Google ADK](https://composio.dev/toolkits/sendloop/framework/google-adk) - [LangChain](https://composio.dev/toolkits/sendloop/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/sendloop/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/sendloop/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/sendloop/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/sendloop/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 Sendloop - 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 Sendloop 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 Sendloop MCP server, and what's possible with it? The Sendloop MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Sendloop account. It provides structured and secure access to your email marketing campaigns, subscriber lists, and detailed reports, so your agent can list campaigns, analyze subscriber data, retrieve account information, and review campaign performance on your behalf. - Comprehensive campaign management: Ask your agent to list all existing email campaigns, filter them by status, and handle pagination to easily browse through your marketing efforts. - Subscriber list access and reporting: Retrieve all your mailing lists and get detailed reports on subscriber growth, engagement, and performance after sending campaigns. - Targeted subscriber insights: Let the agent fetch subscribers for any given list, filter them by status, and manage large lists with effortless pagination. - Account information retrieval: Have your agent pull up-to-date details about your Sendloop account, keeping you informed about your overall setup and usage. - Performance analytics: Quickly get summary metrics for specific subscriber lists to evaluate campaign success and optimize your email marketing strategy. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `SENDLOOP_GET_OVERALL_LIST_REPORT` | Get Overall List Report | Tool to retrieve overall report for a subscriber list. use after sending campaigns to get summary metrics. | | `SENDLOOP_LIST_CAMPAIGNS` | List Campaigns | Tool to list campaigns. use when you need to filter by campaign status and handle pagination for campaign retrieval. | | `SENDLOOP_LIST_LISTS` | List SendLoop Lists | Tool to retrieve subscriber lists. use when you need to get all mailing lists with optional pagination. | | `SENDLOOP_LIST_SUBSCRIBERS` | List SendLoop Subscribers | Tool to list subscribers in a specified sendloop list with pagination. use when you need to retrieve subscribers for a given list id, optionally filtering by status, page number, and page size. | | `SENDLOOP_SENDLOOP_GET_ACCOUNT_INFO` | Get Sendloop Account Information | Tool to retrieve account information. use when you need details about the current sendloop account. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Sendloop MCP server is an implementation of the Model Context Protocol that connects your AI agent to Sendloop. It provides structured and secure access so your agent can perform Sendloop 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 Sendloop - 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 Sendloop - MCPServerStreamableHTTP connects to the Sendloop 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 Sendloop 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 Sendloop composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["sendloop"], ) 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 Sendloop endpoint - The agent uses GPT-5 to interpret user commands and perform Sendloop operations - The instructions field defines the agent's role and behavior ```python # Attach the MCP server to a Pydantic AI Agent sendloop_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[sendloop_mcp], instructions=( "You are a Sendloop assistant. Use Sendloop 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 - Sendloop 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 Sendloop.\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 Sendloop composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["sendloop"], ) 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 sendloop_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[sendloop_mcp], instructions=( "You are a Sendloop assistant. Use Sendloop 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 Sendloop.\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 Sendloop through Composio's Tool Router. With this setup, your agent can perform real Sendloop 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 + Sendloop 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 Sendloop MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/sendloop/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/sendloop/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/sendloop/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/sendloop/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/sendloop/framework/codex) - [OpenClaw](https://composio.dev/toolkits/sendloop/framework/openclaw) - [Hermes](https://composio.dev/toolkits/sendloop/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/sendloop/framework/cli) - [Google ADK](https://composio.dev/toolkits/sendloop/framework/google-adk) - [LangChain](https://composio.dev/toolkits/sendloop/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/sendloop/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/sendloop/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/sendloop/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/sendloop/framework/crew-ai) ## Related Toolkits - [Metaads](https://composio.dev/toolkits/metaads) - Metaads is Meta's official Ads API that lets you manage, analyze, and optimize your Facebook and Instagram ad campaigns. Streamline ad operations and gain deeper insights with robust automation. - [Adrapid](https://composio.dev/toolkits/adrapid) - Adrapid is a platform for rapid creation of digital marketing visuals using templates. It streamlines design workflows for banners, images, and HTML5 content with automation. - [Adyntel](https://composio.dev/toolkits/adyntel) - Adyntel is an API that retrieves LinkedIn ads for any company using a domain or LinkedIn Page ID. Easily access competitive ad intelligence to power your marketing workflows. - [Beaconstac](https://composio.dev/toolkits/beaconstac) - Beaconstac is a platform for creating and managing QR codes and proximity beacons. It helps businesses engage customers and track marketing performance with powerful analytics. - [Campaign cleaner](https://composio.dev/toolkits/campaign_cleaner) - Campaign cleaner is an email campaign optimization tool that boosts compatibility and deliverability across email clients. It helps marketers get better results by cleaning, enhancing, and ensuring high performance for every campaign. - [Deadline funnel](https://composio.dev/toolkits/deadline_funnel) - Deadline Funnel lets you create personalized deadlines and timers for your marketing campaigns. It helps marketers boost conversions by adding authentic urgency to offers. - [Google Ads](https://composio.dev/toolkits/googleads) - Google Ads is Google's online advertising platform for creating, managing, and optimizing digital campaigns. It helps businesses reach targeted customers and maximize return on ad spend. - [Instantly](https://composio.dev/toolkits/instantly) - Instantly is a platform for automating cold email outreach, managing leads, and optimizing deliverability. Get better results from email campaigns with minimal manual effort. - [Proofly](https://composio.dev/toolkits/proofly) - Proofly is a social proof platform that displays real-time notifications of customer activity on your site. It helps you increase website conversions by building trust and urgency for visitors. - [Segmetrics](https://composio.dev/toolkits/segmetrics) - Segmetrics is a marketing analytics platform that reveals detailed insights into your customer journeys. It helps businesses optimize marketing strategies with accurate, actionable reporting. - [Semrush](https://composio.dev/toolkits/semrush) - Semrush is a leading SEO tool suite for keyword research, competitor analysis, and campaign tracking. It empowers marketers to improve search rankings and optimize online visibility. - [Sidetracker](https://composio.dev/toolkits/sidetracker) - Sidetracker is a marketing analytics platform that tracks expenses, sales funnels, and customer journeys. It helps optimize marketing spend and visualize campaign performance from start to finish. - [Stannp](https://composio.dev/toolkits/stannp) - Stannp is an API-driven direct mail platform for sending postcards and letters programmatically. It lets you automate physical mail delivery—no manual printing or mailing required. - [Tapfiliate](https://composio.dev/toolkits/tapfiliate) - Tapfiliate is an affiliate and referral tracking platform for businesses. It helps companies efficiently manage, track, and grow their affiliate programs. - [Tpscheck](https://composio.dev/toolkits/tpscheck) - Tpscheck is a real-time service for verifying UK phone numbers against TPS and CTPS registers. It helps prevent unwanted marketing calls and ensures compliance with UK telemarketing laws. - [Gmail](https://composio.dev/toolkits/gmail) - Gmail is Google's email service with powerful spam protection, search, and G Suite integration. It keeps your inbox organized and makes communication fast and reliable. - [Google Calendar](https://composio.dev/toolkits/googlecalendar) - Google Calendar is a time management service for scheduling meetings, events, and reminders. It streamlines personal and team organization with integrated notifications and sharing options. - [Google Drive](https://composio.dev/toolkits/googledrive) - Google Drive is a cloud storage platform for uploading, sharing, and collaborating on files. It's perfect for keeping your documents accessible and organized across devices. - [Outlook](https://composio.dev/toolkits/outlook) - Outlook is Microsoft's email and calendaring platform for unified communications and scheduling. It helps users stay organized with powerful email, contacts, and calendar management. - [Twitter](https://composio.dev/toolkits/twitter) - Twitter is a social media platform for sharing real-time updates, conversations, and news. Stay connected, informed, and engaged with communities worldwide. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Sendloop MCP? With a standalone Sendloop MCP server, the agents and LLMs can only access a fixed set of Sendloop tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Sendloop 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 Sendloop tools. ### Can I manage the permissions and scopes for Sendloop while using Tool Router? Yes, absolutely. You can configure which Sendloop 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 Sendloop data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)