# How to integrate Serply MCP with Pydantic AI ```json { "title": "How to integrate Serply MCP with Pydantic AI", "toolkit": "Serply", "toolkit_slug": "serply", "framework": "Pydantic AI", "framework_slug": "pydantic-ai", "url": "https://composio.dev/toolkits/serply/framework/pydantic-ai", "markdown_url": "https://composio.dev/toolkits/serply/framework/pydantic-ai.md", "updated_at": "2026-05-12T10:25:38.612Z" } ``` ## Introduction This guide walks you through connecting Serply to Pydantic AI using the Composio tool router. By the end, you'll have a working Serply agent that can find top news articles on ai today, get latest product prices for smartwatches, search for job listings in san francisco through natural language commands. This guide will help you understand how to give your Pydantic AI agent real control over a Serply account through Composio's Serply MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Serply with - [OpenAI Agents SDK](https://composio.dev/toolkits/serply/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/serply/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/serply/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/serply/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/serply/framework/codex) - [OpenClaw](https://composio.dev/toolkits/serply/framework/openclaw) - [Hermes](https://composio.dev/toolkits/serply/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/serply/framework/cli) - [Google ADK](https://composio.dev/toolkits/serply/framework/google-adk) - [LangChain](https://composio.dev/toolkits/serply/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/serply/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/serply/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/serply/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/serply/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 Serply - 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 Serply 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 Serply MCP server, and what's possible with it? The Serply MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Serply account. It provides structured and secure access to search engine results—including web, news, video, and product searches—so your agent can perform actions like querying search engines, retrieving news headlines, finding videos, and exploring product listings on your behalf. - Web search automation: Let your agent run web queries and return structured search results for any keyword or topic. - Real-time news discovery: Fetch the latest news articles and headlines from major sources, filtered by topic or region. - Video content search: Find relevant videos across platforms using keyword-based queries and filter by date or relevance. - Product and job listing retrieval: Search for products or job postings to quickly gather marketplace or employment data. - Image and map search capabilities: Enable your agent to pull images or map results, perfect for visual or location-based queries. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `SERPLY_PERFORM_IMAGE_SEARCH` | Perform Image Search | Performs an image search using the Serply API to find images matching a text query. This tool searches for images on the web and returns results with image URLs, thumbnails, dimensions, titles, and source information. Ideal for finding visual content, gathering image references, or discovering images related to specific topics or keywords. Use this when you need to: - Find images matching specific descriptions or keywords - Gather visual references for a topic - Retrieve image URLs for display or download - Search for images with specific characteristics Supports pagination, localization (language/country), and safe search filtering. | | `SERPLY_PERFORM_MAPS_SEARCH` | Perform Maps Search | Tool to perform a maps search. Use when you need to find geographic locations for a given query. | | `SERPLY_PERFORM_SCHOLAR_SEARCH` | Perform Scholar Search | Tool to perform an academic scholar search via Serply. Use when you need scholarly literature search results for a specific query. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Serply MCP server is an implementation of the Model Context Protocol that connects your AI agent to Serply. It provides structured and secure access so your agent can perform Serply 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 Serply - 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 Serply - MCPServerStreamableHTTP connects to the Serply 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 Serply 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 Serply composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["serply"], ) 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 Serply endpoint - The agent uses GPT-5 to interpret user commands and perform Serply operations - The instructions field defines the agent's role and behavior ```python # Attach the MCP server to a Pydantic AI Agent serply_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[serply_mcp], instructions=( "You are a Serply assistant. Use Serply 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 - Serply 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 Serply.\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 Serply composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["serply"], ) 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 serply_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[serply_mcp], instructions=( "You are a Serply assistant. Use Serply 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 Serply.\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 Serply through Composio's Tool Router. With this setup, your agent can perform real Serply 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 + Serply 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 Serply MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/serply/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/serply/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/serply/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/serply/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/serply/framework/codex) - [OpenClaw](https://composio.dev/toolkits/serply/framework/openclaw) - [Hermes](https://composio.dev/toolkits/serply/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/serply/framework/cli) - [Google ADK](https://composio.dev/toolkits/serply/framework/google-adk) - [LangChain](https://composio.dev/toolkits/serply/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/serply/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/serply/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/serply/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/serply/framework/crew-ai) ## Related Toolkits - [Excel](https://composio.dev/toolkits/excel) - Microsoft Excel is a robust spreadsheet application for organizing, analyzing, and visualizing data. 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It helps streamline how you gather, organize, and analyze responses. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Serply MCP? With a standalone Serply MCP server, the agents and LLMs can only access a fixed set of Serply tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Serply 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 Serply tools. ### Can I manage the permissions and scopes for Serply while using Tool Router? Yes, absolutely. You can configure which Serply 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 Serply data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)