SIGN UPLOG IN
X (Twitter)LinkedInGitHubDiscordYouTube

How to integrate Prerender MCP with Pydantic AI

Connect Pydantic AI to Prerender MCP. Fetch static html for your homepage, get prerendered content for blog post, and more using natural language, with authentication handled for you.

Get started for freeGet a demo
Prerender logoPrerender
Api Key

Prerender.io is a service that pre-renders JavaScript-heavy websites for SEO. It lets you serve fast, static HTML versions to search engine crawlers to boost discoverability.

10 Tools

Introduction

This guide walks you through connecting Prerender to Pydantic AI using the Composio tool router. By the end, you'll have a working Prerender agent that can recache URLs, clear the cache, search cached URLs, create SEO audit reports, and adjust recache speed through natural language commands.

This guide will help you understand how to give your Pydantic AI agent real control over a Prerender account through Composio's Prerender MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

Also integrate Prerender with

Claude CodeClaude CoworkOpenAI Agents SDKClaude Agent SDKGrok BotCodexOpenClawHermesAtomic AgentGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAIAutoGen

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 Prerender
  • 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 Prerender 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 Prerender MCP server, and what's possible with it?

The Prerender MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Prerender account. It provides structured and secure access to your prerendered website snapshots, so your agent can fetch static HTML versions of your JavaScript-heavy pages, check SEO visibility, monitor crawler access, and automate site snapshot retrieval on your behalf.

  • Fetch prerendered HTML snapshots: Instantly retrieve static HTML versions of dynamic or JavaScript-rich pages for any given URL.
  • Automate SEO monitoring: Let your agent check how search engines will see your site by pulling the exact prerendered output served to crawlers.
  • Verify page rendering consistency: Use the agent to compare prerendered snapshots across multiple URLs or timeframes, keeping your content SEO-friendly and up to date.
  • Monitor site availability for crawlers: Have your agent ensure that key pages are accessible and properly rendered for search engines, alerting you to any issues.
  • Enable hands-free content auditing: Schedule or trigger regular snapshot fetches so your team can quickly audit site structure and indexed content—no manual browser tests required.

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

Composio's Composio SDK helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Step by step09 STEPS
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
2

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard 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.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.
3

Install dependencies

bash
pip install composio pydantic-ai python-dotenv

Install the required libraries.

What's happening:

  • composio connects your agent to external SaaS tools like Prerender
  • pydantic-ai lets you create structured AI agents with tool support
  • python-dotenv loads your environment variables securely from a .env file
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key

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
5

Import dependencies

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()
What's happening:
  • We load environment variables and import required modules
  • Composio manages connections to Prerender
  • MCPServerStreamableHTTP connects to the Prerender MCP server endpoint
  • Agent from Pydantic AI lets you define and run the AI assistant
6

Create a Tool Router Session

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 Prerender
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["prerender"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")
What's happening:
  • We're creating a Tool Router session that gives your agent access to Prerender 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
7

Initialize the Pydantic AI Agent

python
# Attach the MCP server to a Pydantic AI Agent
prerender_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[prerender_mcp],
    instructions=(
        "You are a Prerender assistant. Use Prerender tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the Prerender endpoint
  • The agent uses GPT-5 to interpret user commands and perform Prerender operations
  • The instructions field defines the agent's role and behavior
8

Build the chat interface

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 Prerender.\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()
What's happening:
  • The agent reads input from the terminal and streams its response
  • Prerender API calls happen automatically under the hood
  • The model keeps conversation history to maintain context across turns
9

Run the application

python
if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • The asyncio loop launches the agent and keeps it running until you exit

Complete Code

Here's the complete code to get you started with Prerender and Pydantic AI:

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 Prerender
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["prerender"],
    )
    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
    prerender_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[prerender_mcp],
        instructions=(
            "You are a Prerender assistant. Use Prerender 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 Prerender.\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 Prerender through Composio's Tool Router. With this setup, your agent can perform real Prerender 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 + Prerender for workflow automation)
This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.
TOOLS

Supported Tools

Every Prerender action and event your agent gets out of the box.

Change Recache Speed

Adjust the rendering speed of Prerender's Manual/API recache queue to control how fast it processes URLs.

Check Health

Tool to check the health status of the Prerender API service.

Clear Cache

Tool to clear Prerender cache using SQL-like wildcard patterns.

Create SEO Audit Report

Tool to generate SEO audit reports for a specific URL.

Get Cache Clear Status

Tool to check the status of a cache clear job.

Get Prerendered Page

Fetch the prerendered HTML snapshot for a specified URL.

List Healthz

Tool to check Prerender API health and availability.

List V3

Tool to get a greeting message from the Prerender API.

Recache URL

Tool to cache or recache URLs in Prerender.

Search Cached URLs

Tool to search for cached URLs in your Prerender account and view their cache status.

FRAMEWORKS

How to build Prerender MCP Agent with another framework

Claude Code logo

Claude Code

Use Prerender MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Prerender MCP with Claude Cowork

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Prerender MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Prerender MCP with Claude Agent SDK

Grok Bot logo

Grok Bot

Use Prerender MCP with Grok Bot

Codex logo

Codex

Use Prerender MCP with Codex

OpenClaw logo

OpenClaw

Use Prerender MCP with OpenClaw

Hermes logo

Hermes

Use Prerender MCP with Hermes

Atomic Agent logo

Atomic Agent

Use Prerender MCP with Atomic Agent

Google ADK logo

Google ADK

Use Prerender MCP with Google ADK

LangChain logo

LangChain

Use Prerender MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Prerender MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Prerender MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Prerender MCP with LlamaIndex

CrewAI logo

CrewAI

Use Prerender MCP with CrewAI

AutoGen logo

AutoGen

Use Prerender MCP with AutoGen

FAQ

Frequently asked questions

With a standalone Prerender MCP server, the agents and LLMs can only access a fixed set of Prerender tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Prerender and many other apps based on the task at hand, all through a single MCP endpoint.

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 Prerender tools.

Yes, absolutely. You can configure which Prerender 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.

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 Prerender data and credentials are handled as safely as possible.

Start with Prerender.It takes 30 seconds.

Managed auth, hosted MCP servers, and every Prerender tool your agent needs.Free to start.

Start building