# How to integrate Klazify MCP with Pydantic AI ```json { "title": "How to integrate Klazify MCP with Pydantic AI", "toolkit": "Klazify", "toolkit_slug": "klazify", "framework": "Pydantic AI", "framework_slug": "pydantic-ai", "url": "https://composio.dev/toolkits/klazify/framework/pydantic-ai", "markdown_url": "https://composio.dev/toolkits/klazify/framework/pydantic-ai.md", "updated_at": "2026-03-29T06:39:37.234Z" } ``` ## Introduction This guide walks you through connecting Klazify to Pydantic AI using the Composio tool router. By the end, you'll have a working Klazify agent that can categorize https://example.com and get its logo, extract social media links for a company website, identify technology stack of a given domain through natural language commands. This guide will help you understand how to give your Pydantic AI agent real control over a Klazify account through Composio's Klazify MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Klazify with - [OpenAI Agents SDK](https://composio.dev/toolkits/klazify/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/klazify/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/klazify/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/klazify/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/klazify/framework/codex) - [OpenClaw](https://composio.dev/toolkits/klazify/framework/openclaw) - [Hermes](https://composio.dev/toolkits/klazify/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/klazify/framework/cli) - [Google ADK](https://composio.dev/toolkits/klazify/framework/google-adk) - [LangChain](https://composio.dev/toolkits/klazify/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/klazify/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/klazify/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/klazify/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/klazify/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 Klazify - 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 Klazify 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 Klazify MCP server, and what's possible with it? The Klazify MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Klazify account. It provides structured and secure access so your agent can perform Klazify operations on your behalf. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `KLAZIFY_CATEGORIZE_URL` | Categorize URL | Tool to retrieve IAB and Klazify category classifications for a specified domain or URL with confidence scores. Use when you need to categorize websites into 620+ IAB V3 categories using machine learning, or obtain detailed domain information including company data and social media links. | | `KLAZIFY_GET_COMPANY_DATA` | Get Company Data | Tool to retrieve comprehensive company information for a specified domain including business data, location, employee count, revenue, funding, and industry classifications. Use when you need detailed company profile information from a domain URL. | | `KLAZIFY_GET_DOMAIN_EXPIRATION` | Get Domain Expiration | Tool to retrieve domain registration and expiration information for a specified domain. Use when you need to check domain age, registration date, expiration date, or days until expiration. | | `KLAZIFY_GET_DOMAIN_LOGO` | Get Domain Logo | Tool to obtain the logo URL associated with a given domain. Use when you need to retrieve a company's logo from their website URL. | | `KLAZIFY_GET_SIMILAR_COMPANIES` | Get Similar Companies | Tool to identify companies similar to the specified domain by analyzing category and target market. Use when you need to find competitors or similar businesses to a given domain. | | `KLAZIFY_GET_SOCIAL_MEDIA_LINKS` | Get Social Media Links | Tool to retrieve the list of social media links for a given domain. Use when you need to extract social media profile URLs across multiple platforms (Facebook, Twitter, Instagram, LinkedIn, YouTube, Medium, GitHub, Pinterest). | | `KLAZIFY_GET_TECH_STACK` | Get Tech Stack | Tool to retrieve the technological stack utilized by a website including frameworks, platforms, and services. Use when you need to identify what technologies a domain uses for competitive analysis, lead generation, or market research. | | `KLAZIFY_REAL_TIME_CATEGORIZATION` | Real Time Categorization | Tool to perform real-time website categorization with immediate AI-powered analysis and classification. Use when you need instant domain categorization into 621+ IAB V3 categories with confidence scores, along with company data, social media profiles, and technology stack information. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Klazify MCP server is an implementation of the Model Context Protocol that connects your AI agent to Klazify. It provides structured and secure access so your agent can perform Klazify 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 Klazify - 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 Klazify - MCPServerStreamableHTTP connects to the Klazify 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 Klazify 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 Klazify composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["klazify"], ) 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 Klazify endpoint - The agent uses GPT-5 to interpret user commands and perform Klazify operations - The instructions field defines the agent's role and behavior ```python # Attach the MCP server to a Pydantic AI Agent klazify_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[klazify_mcp], instructions=( "You are a Klazify assistant. Use Klazify 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 - Klazify 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 Klazify.\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 Klazify composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["klazify"], ) 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 klazify_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[klazify_mcp], instructions=( "You are a Klazify assistant. Use Klazify 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 Klazify.\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 Klazify through Composio's Tool Router. With this setup, your agent can perform real Klazify 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 + Klazify 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 Klazify MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/klazify/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/klazify/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/klazify/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/klazify/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/klazify/framework/codex) - [OpenClaw](https://composio.dev/toolkits/klazify/framework/openclaw) - [Hermes](https://composio.dev/toolkits/klazify/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/klazify/framework/cli) - [Google ADK](https://composio.dev/toolkits/klazify/framework/google-adk) - [LangChain](https://composio.dev/toolkits/klazify/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/klazify/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/klazify/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/klazify/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/klazify/framework/crew-ai) ## Related Toolkits - [Composio](https://composio.dev/toolkits/composio) - Composio is an integration platform that connects AI agents with hundreds of business tools. It streamlines authentication and lets you trigger actions across services—no custom code needed. - [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. - [Composio search](https://composio.dev/toolkits/composio_search) - Composio search is a unified web search toolkit spanning travel, e-commerce, news, financial markets, images, and more. It lets you and your apps tap into up-to-date web data from a single, easy-to-integrate service. - [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. - [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. - [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. - [Perplexityai](https://composio.dev/toolkits/perplexityai) - Perplexityai delivers natural, conversational AI models for generating human-like text. Instantly get context-aware, high-quality responses for chat, search, or complex workflows. - [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. - [Browser tool](https://composio.dev/toolkits/browser_tool) - Browser tool is a virtual browser integration that lets AI agents interact with the web programmatically. It enables automated browsing, scraping, and action-taking from any AI workflow. - [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. - [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. - [Ai ml api](https://composio.dev/toolkits/ai_ml_api) - Ai ml api is a suite of AI/ML models for natural language and image tasks. It provides fast, scalable access to advanced AI capabilities for your apps and workflows. - [Aivoov](https://composio.dev/toolkits/aivoov) - Aivoov is an AI-powered text-to-speech platform offering 1,000+ voices in over 150 languages. Instantly turn written content into natural, human-like audio for any application. - [All images ai](https://composio.dev/toolkits/all_images_ai) - All-Images.ai is an AI-powered image generation and management platform. It helps you create, search, and organize images effortlessly with advanced AI capabilities. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Klazify MCP? With a standalone Klazify MCP server, the agents and LLMs can only access a fixed set of Klazify tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Klazify 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 Klazify tools. ### Can I manage the permissions and scopes for Klazify while using Tool Router? Yes, absolutely. You can configure which Klazify 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 Klazify data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)