# How to integrate LeadBoxer MCP with Pydantic AI ```json { "title": "How to integrate LeadBoxer MCP with Pydantic AI", "toolkit": "LeadBoxer", "toolkit_slug": "leadboxer", "framework": "Pydantic AI", "framework_slug": "pydantic-ai", "url": "https://composio.dev/toolkits/leadboxer/framework/pydantic-ai", "markdown_url": "https://composio.dev/toolkits/leadboxer/framework/pydantic-ai.md", "updated_at": "2026-03-29T06:40:06.775Z" } ``` ## Introduction This guide walks you through connecting LeadBoxer to Pydantic AI using the Composio tool router. By the end, you'll have a working LeadBoxer agent that can list all new leads from today, show all companies visiting pricing page, get contact info for most recent lead through natural language commands. This guide will help you understand how to give your Pydantic AI agent real control over a LeadBoxer account through Composio's LeadBoxer MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate LeadBoxer with - [ChatGPT](https://composio.dev/toolkits/leadboxer/framework/chatgpt) - [Antigravity](https://composio.dev/toolkits/leadboxer/framework/antigravity) - [OpenAI Agents SDK](https://composio.dev/toolkits/leadboxer/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/leadboxer/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/leadboxer/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/leadboxer/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/leadboxer/framework/codex) - [OpenClaw](https://composio.dev/toolkits/leadboxer/framework/openclaw) - [Hermes](https://composio.dev/toolkits/leadboxer/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/leadboxer/framework/cli) - [Google ADK](https://composio.dev/toolkits/leadboxer/framework/google-adk) - [LangChain](https://composio.dev/toolkits/leadboxer/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/leadboxer/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/leadboxer/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/leadboxer/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/leadboxer/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 LeadBoxer - 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 LeadBoxer 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 LeadBoxer MCP server, and what's possible with it? The LeadBoxer MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your LeadBoxer account. It provides structured and secure access so your agent can perform LeadBoxer operations on your behalf. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `LEADBOXER_ADD_OR_UPDATE_LEAD_TAGS` | Add or Update Lead Tags | Tool to add or update lead tags in LeadBoxer. Use when you need to manage lead tags by adding new tags, removing specific tags, or overwriting all existing tags for a specified user. | | `LEADBOXER_DELETE_CTD` | Delete Custom Tracking Domain | Tool to delete a custom tracking domain entry for a dataset. Use when you need to remove a specific custom tracking domain (CTD) associated with a dataset in LeadBoxer. | | `LEADBOXER_GET_EVENTS` | Get Events | Tool to fetch events for specified sessions from LeadBoxer. Use when you need to retrieve behavioral data including pageviews, clicks, form submissions, email interactions, and custom events. Events can be filtered by session ID, email, user ID, or segment/smartlist IDs. | | `LEADBOXER_GET_LEAD_SCORE_FORMULA` | Get Lead Score Formula | Tool to fetch the lead score formula for a specific dataset. Use when you need to understand how lead scores are calculated for records in a dataset. The formula defines scoring based on criteria types: Range (number ranges), Match (exact values), Exists (presence of values), and Boost (event-based scoring). | | `LEADBOXER_GET_SESSIONS` | Get Sessions | Tool to fetch sessions for a specified lead ID from LeadBoxer. Use when you need to retrieve session data for a user, with optional filtering by email, user ID, Smartlist ID, or segment ID. A session represents a single visit to the site, and users can have multiple sessions over time. | | `LEADBOXER_LOG_SERVER_SIDE_EVENT` | Log Server-Side Event | Tool to track server-side events in LeadBoxer. Use when tracking backend events, page views, or custom activities from your server. This endpoint supports tracking user interactions, conversions, and other activities that occur on the server-side. | | `LEADBOXER_GET_CUSTOM_TRACKING_DOMAINS` | Get Custom Tracking Domains | Tool to fetch custom tracking domain entries for a dataset. Use when you need to retrieve all custom tracking domains that are created or in progress for a specific datasetId. | | `LEADBOXER_POST_EVENT_DATA` | Post Event Data | Tool to send event data for tracking user activities via POST request. Use when tracking events by sending data in the request body with application/x-www-form-urlencoded format. | | `LEADBOXER_GET_LEAD_DETAIL` | Get Lead Detail | Tool to fetch detailed information about a lead based on filters. Use when you need comprehensive lead data for a specific lead ID. The default view type is B2B. Note: On initial pageview, there may be a few seconds overhead before data is populated; consider implementing a 3-second delay after lead creation. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The LeadBoxer MCP server is an implementation of the Model Context Protocol that connects your AI agent to LeadBoxer. It provides structured and secure access so your agent can perform LeadBoxer 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 LeadBoxer - 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 LeadBoxer - MCPServerStreamableHTTP connects to the LeadBoxer 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 LeadBoxer 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 LeadBoxer composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["leadboxer"], ) 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 LeadBoxer endpoint - The agent uses GPT-5 to interpret user commands and perform LeadBoxer operations - The instructions field defines the agent's role and behavior ```python # Attach the MCP server to a Pydantic AI Agent leadboxer_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[leadboxer_mcp], instructions=( "You are a LeadBoxer assistant. Use LeadBoxer 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 - LeadBoxer 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 LeadBoxer.\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 LeadBoxer composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["leadboxer"], ) 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 leadboxer_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[leadboxer_mcp], instructions=( "You are a LeadBoxer assistant. Use LeadBoxer 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 LeadBoxer.\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 LeadBoxer through Composio's Tool Router. With this setup, your agent can perform real LeadBoxer 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 + LeadBoxer 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 LeadBoxer MCP Agent with another framework - [ChatGPT](https://composio.dev/toolkits/leadboxer/framework/chatgpt) - [Antigravity](https://composio.dev/toolkits/leadboxer/framework/antigravity) - [OpenAI Agents SDK](https://composio.dev/toolkits/leadboxer/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/leadboxer/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/leadboxer/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/leadboxer/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/leadboxer/framework/codex) - [OpenClaw](https://composio.dev/toolkits/leadboxer/framework/openclaw) - [Hermes](https://composio.dev/toolkits/leadboxer/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/leadboxer/framework/cli) - [Google ADK](https://composio.dev/toolkits/leadboxer/framework/google-adk) - [LangChain](https://composio.dev/toolkits/leadboxer/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/leadboxer/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/leadboxer/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/leadboxer/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/leadboxer/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. - [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. - [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. - [Addressfinder](https://composio.dev/toolkits/addressfinder) - Addressfinder is a data quality platform for verifying addresses, emails, and phone numbers. It helps you ensure accurate customer and contact data every time. - [Aeroleads](https://composio.dev/toolkits/aeroleads) - Aeroleads is a B2B lead generation platform for finding business emails and phone numbers. Grow your sales pipeline faster with powerful prospecting tools. - [Agiled](https://composio.dev/toolkits/agiled) - Agiled is an all-in-one business management platform for CRM, projects, and finance. It helps you streamline workflows, consolidate client data, and manage business processes in one place. - [Amplitude](https://composio.dev/toolkits/amplitude) - Amplitude is a digital analytics platform for product and behavioral data insights. It helps teams analyze user journeys and make data-driven decisions quickly. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and LeadBoxer MCP? With a standalone LeadBoxer MCP server, the agents and LLMs can only access a fixed set of LeadBoxer tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from LeadBoxer 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 LeadBoxer tools. ### Can I manage the permissions and scopes for LeadBoxer while using Tool Router? Yes, absolutely. You can configure which LeadBoxer 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 LeadBoxer data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)