# How to integrate Screenshot fyi MCP with Pydantic AI

```json
{
  "title": "How to integrate Screenshot fyi MCP with Pydantic AI",
  "toolkit": "Screenshot fyi",
  "toolkit_slug": "screenshot_fyi",
  "framework": "Pydantic AI",
  "framework_slug": "pydantic-ai",
  "url": "https://composio.dev/toolkits/screenshot_fyi/framework/pydantic-ai",
  "markdown_url": "https://composio.dev/toolkits/screenshot_fyi/framework/pydantic-ai.md",
  "updated_at": "2026-05-12T10:24:54.755Z"
}
```

## Introduction

This guide walks you through connecting Screenshot fyi to Pydantic AI using the Composio tool router. By the end, you'll have a working Screenshot fyi agent that can capture homepage screenshot of competitor website, take mobile view screenshot of landing page, get screenshot of website after login through natural language commands.
This guide will help you understand how to give your Pydantic AI agent real control over a Screenshot fyi account through Composio's Screenshot fyi MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Screenshot fyi with

- [OpenAI Agents SDK](https://composio.dev/toolkits/screenshot_fyi/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/screenshot_fyi/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/screenshot_fyi/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/screenshot_fyi/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/screenshot_fyi/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/screenshot_fyi/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/screenshot_fyi/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/screenshot_fyi/framework/cli)
- [Google ADK](https://composio.dev/toolkits/screenshot_fyi/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/screenshot_fyi/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/screenshot_fyi/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/screenshot_fyi/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/screenshot_fyi/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/screenshot_fyi/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 Screenshot fyi
- 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 Screenshot fyi 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 Screenshot fyi MCP server, and what's possible with it?

The Screenshot fyi MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Screenshot fyi account. It provides structured and secure access to fast, high-quality screenshot generation for any website, so your agent can capture website snapshots, archive web content, and automate visual reporting tasks on your behalf.
- Instant website screenshot capture: Let your agent take full-page or viewport screenshots of any public website with a single command.
- Visual monitoring and archiving: Enable automated visual archiving of webpages for compliance, content tracking, or change monitoring without manual effort.
- Automated website previews for reports: Effortlessly generate updated website thumbnails or previews to embed in presentations, documentation, or status reports.
- Streamlined UI testing and validation: Capture snapshots for UI regression tests, helping you keep a visual log of changes and spot differences over time.
- Content preservation and backups: Save snapshots of important web content before changes or for backup purposes, ensuring you always have a visual record when you need it.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `SCREENSHOT_FYI_TAKE_SCREENSHOT` | Take Screenshot | Tool to capture a webpage screenshot. Use after specifying the target URL and options. JavaScript-heavy pages may capture before full render; ensure the page is fully loaded prior to capture. |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Screenshot fyi MCP server is an implementation of the Model Context Protocol that connects your AI agent to Screenshot fyi. It provides structured and secure access so your agent can perform Screenshot fyi 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 Screenshot fyi
- 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 Screenshot fyi
- MCPServerStreamableHTTP connects to the Screenshot fyi 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 Screenshot fyi 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 Screenshot fyi
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["screenshot_fyi"],
    )
    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 Screenshot fyi endpoint
- The agent uses GPT-5 to interpret user commands and perform Screenshot fyi operations
- The instructions field defines the agent's role and behavior
```python
# Attach the MCP server to a Pydantic AI Agent
screenshot_fyi_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[screenshot_fyi_mcp],
    instructions=(
        "You are a Screenshot fyi assistant. Use Screenshot fyi 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
- Screenshot fyi 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 Screenshot fyi.\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 Screenshot fyi
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["screenshot_fyi"],
    )
    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
    screenshot_fyi_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[screenshot_fyi_mcp],
        instructions=(
            "You are a Screenshot fyi assistant. Use Screenshot fyi 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 Screenshot fyi.\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 Screenshot fyi through Composio's Tool Router. With this setup, your agent can perform real Screenshot fyi 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 + Screenshot fyi 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 Screenshot fyi MCP Agent with another framework

- [OpenAI Agents SDK](https://composio.dev/toolkits/screenshot_fyi/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/screenshot_fyi/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/screenshot_fyi/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/screenshot_fyi/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/screenshot_fyi/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/screenshot_fyi/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/screenshot_fyi/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/screenshot_fyi/framework/cli)
- [Google ADK](https://composio.dev/toolkits/screenshot_fyi/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/screenshot_fyi/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/screenshot_fyi/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/screenshot_fyi/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/screenshot_fyi/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/screenshot_fyi/framework/crew-ai)

## Related Toolkits

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- [Ably](https://composio.dev/toolkits/ably) - Ably is a real-time messaging platform for live chat and data sync in modern apps. It offers global scale and rock-solid reliability for seamless, instant experiences.
- [Abuselpdb](https://composio.dev/toolkits/abuselpdb) - Abuselpdb is a central database for reporting and checking IPs linked to malicious online activity. Use it to quickly identify and report suspicious or abusive IP addresses.
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- [Anchor browser](https://composio.dev/toolkits/anchor_browser) - Anchor browser is a developer platform for AI-powered web automation. It transforms complex browser actions into easy API endpoints for streamlined web interaction.
- [Apiflash](https://composio.dev/toolkits/apiflash) - Apiflash is a website screenshot API for programmatically capturing web pages. It delivers high-quality screenshots on demand for automation, monitoring, or reporting.
- [Apiverve](https://composio.dev/toolkits/apiverve) - Apiverve delivers a suite of powerful APIs that simplify integration for developers. It's designed for reliability and scalability so you can build faster, smarter applications without the integration headache.
- [Appcircle](https://composio.dev/toolkits/appcircle) - Appcircle is an enterprise-grade mobile CI/CD platform for building, testing, and publishing mobile apps. It streamlines mobile DevOps so teams ship faster and with more confidence.
- [Appdrag](https://composio.dev/toolkits/appdrag) - Appdrag is a cloud platform for building websites, APIs, and databases with drag-and-drop tools and code editing. It accelerates development and iteration by combining hosting, database management, and low-code features in one place.
- [Appveyor](https://composio.dev/toolkits/appveyor) - AppVeyor is a cloud-based continuous integration service for building, testing, and deploying applications. It helps developers automate and streamline their software delivery pipelines.
- [Backendless](https://composio.dev/toolkits/backendless) - Backendless is a backend-as-a-service platform for mobile and web apps, offering database, file storage, user authentication, and APIs. It helps developers ship scalable applications faster without managing server infrastructure.
- [Baserow](https://composio.dev/toolkits/baserow) - Baserow is an open-source no-code database platform for building collaborative data apps. It makes it easy for teams to organize data and automate workflows without writing code.
- [Bench](https://composio.dev/toolkits/bench) - Bench is a benchmarking tool for automated performance measurement and analysis. It helps you quickly evaluate, compare, and track your systems or workflows.
- [Better stack](https://composio.dev/toolkits/better_stack) - Better Stack is a monitoring, logging, and incident management solution for apps and services. It helps teams ensure application reliability and performance with real-time insights.
- [Bitbucket](https://composio.dev/toolkits/bitbucket) - Bitbucket is a Git-based code hosting and collaboration platform for teams. It enables secure repository management and streamlined code reviews.
- [Blazemeter](https://composio.dev/toolkits/blazemeter) - Blazemeter is a continuous testing platform for web and mobile app performance. It empowers teams to automate and analyze large-scale tests with ease.
- [Blocknative](https://composio.dev/toolkits/blocknative) - Blocknative delivers real-time mempool monitoring and transaction management for public blockchains. Instantly track pending transactions and optimize blockchain interactions with live data.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Screenshot fyi MCP?

With a standalone Screenshot fyi MCP server, the agents and LLMs can only access a fixed set of Screenshot fyi tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Screenshot fyi 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 Screenshot fyi tools.

### Can I manage the permissions and scopes for Screenshot fyi while using Tool Router?

Yes, absolutely. You can configure which Screenshot fyi 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 Screenshot fyi data and credentials are handled as safely as possible.

---
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