How to integrate Firecrawl MCP with Pydantic AI

This guide walks you through connecting Firecrawl to Pydantic AI using the Composio tool router. By the end, you'll have a working Firecrawl agent that can extract all product prices from this e-commerce site, crawl competitor blogs for latest article summaries, map all subpages linked from homepage url through natural language commands. This guide will help you understand how to give your Pydantic AI agent real control over a Firecrawl account through Composio's Firecrawl MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

Get started for free Get a demo

Firecrawl

Api Key

Firecrawl automates large-scale web crawling and data extraction. It helps organizations efficiently gather, index, and analyze content from online sources.

29 Tools

Managed auth

Connect Firecrawl without auth hassles

We manage OAuth, API keys, token refresh, and scopes — you just build.

Try for free

Introduction

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

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

Also integrate Firecrawl with

ChatGPT OpenAI Agents SDK Claude Agent SDK Claude Code Claude Cowork Codex OpenCode Cursor VS Code OpenClaw Hermes CLI Google ADK LangChain Vercel AI SDK Mastra AI LlamaIndex CrewAI

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 Firecrawl
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 Firecrawl 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 Firecrawl MCP server, and what's possible with it?

The Firecrawl MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Firecrawl account. It provides structured and secure access to automated web crawling, scraping, and data extraction, so your agent can perform actions like indexing sites, extracting structured content, mapping URLs, and searching the web on your behalf.

Automated web crawling and indexing: Let your agent launch and manage web crawl jobs to gather content or index entire websites efficiently.
Structured data extraction: Instruct your agent to extract targeted data from web pages using custom prompts or schemas, turning unstructured sites into actionable information.
URL mapping and discovery: Have the agent explore and map all URLs within a website, including options for subdomain inclusion, sitemap processing, or search-based discovery.
On-demand scraping and content retrieval: Enable your agent to scrape specific URLs, retrieve page content, and even extract structured JSON using LLM-powered methods.
Integrated web search and data collection: Task your agent with running web searches, scraping top result pages, and returning relevant details—all in one workflow.

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:

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

Step-by-step Guide

Step by step09 STEPS

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

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.

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 Firecrawl
pydantic-ai lets you create structured AI agents with tool support
python-dotenv loads your environment variables securely from a .env file

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

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 Firecrawl
MCPServerStreamableHTTP connects to the Firecrawl MCP server endpoint
Agent from Pydantic AI lets you define and run the AI assistant

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 Firecrawl
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["firecrawl"],
    )
    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 Firecrawl 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

Initialize the Pydantic AI Agent

python

# Attach the MCP server to a Pydantic AI Agent
firecrawl_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[firecrawl_mcp],
    instructions=(
        "You are a Firecrawl assistant. Use Firecrawl tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)

What's happening:

The MCP client connects to the Firecrawl endpoint
The agent uses GPT-5 to interpret user commands and perform Firecrawl operations
The instructions field defines the agent's role and behavior

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 Firecrawl.\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
Firecrawl API calls happen automatically under the hood
The model keeps conversation history to maintain context across turns

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 Firecrawl 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 Firecrawl
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["firecrawl"],
    )
    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
    firecrawl_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[firecrawl_mcp],
        instructions=(
            "You are a Firecrawl assistant. Use Firecrawl 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 Firecrawl.\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 Firecrawl through Composio's Tool Router. With this setup, your agent can perform real Firecrawl 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 + Firecrawl 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 Firecrawl action and event your agent gets out of the box.

Cancel an agent job

Tool to cancel an in-progress agent job by its ID.

Batch scrape multiple URLs

Tool to scrape multiple URLs in batch with concurrent processing.

Cancel a batch scrape job

Tool to cancel a running batch scrape job using its unique identifier.

Get batch scrape status

Retrieves the current status and results of a batch scrape job using the job ID.

Get errors from batch scrape job

Tool to retrieve error details from a batch scrape job, including failed URLs and URLs blocked by robots.

Start a web crawl

Initiates a Firecrawl web crawl from a given URL, applying various filtering and content extraction rules, and polls until the job is complete; ensure the URL is accessible and any regex patterns for paths are valid.

Cancel a crawl job

Cancels an active or queued web crawl job using its ID; attempting to cancel completed, failed, or previously canceled jobs will not change their state.

Cancel a crawl job

Tool to cancel a running crawl job by its ID.

Get crawl job status

Tool to retrieve the status and results of a Firecrawl crawl job.

Get errors from a crawl job

Tool to retrieve errors from a Firecrawl crawl job.

Get all active crawl jobs

Tool to retrieve all active crawl jobs for the authenticated team.

Preview crawl parameters

Preview crawl parameters before starting a crawl by generating optimal configuration from natural language instructions.

Start a web crawl (v2) [NEW]

[NEW v2 API] Initiates a Firecrawl v2 web crawl with enhanced features over v1: natural language prompts for automatic crawler configuration, crawlEntireDomain for sibling/parent page discovery, better depth control with maxDiscoveryDepth, subdomain support, and full webhook configuration.

Get team credit usage

Tool to get current team credit usage information.

Get historical team credit usage

Tool to retrieve historical team credit usage on a monthly basis.

Extract structured data

Extracts structured data from web pages by initiating an extraction job and polling for completion; requires a natural language `prompt` or a JSON `schema` (one must be provided).

Get extract job status

Tool to retrieve the status and results of a previously submitted extract job.

Get agent job status

Tool to get the status and results of an agent job.

Get deep research status

Retrieves the status and results of a deep research job by its ID.

Get the status of a crawl job

Retrieves the current status, progress, and details of a web crawl job, using the job ID obtained when the crawl was initiated.

Generate LLMs.txt for a website

Initiates an async job to generate an LLMs.

Get LLMs.txt generation job status

Tool to get the status and results of an LLMs.

Map multiple URLs

Maps a website by discovering URLs from a starting base URL, with options to customize the crawl via search query, subdomain inclusion, sitemap handling, and result limits; search effectiveness is site-dependent.

Get team queue status

Tool to retrieve metrics about the team's scrape queue.

Scrape URL

Scrapes a publicly accessible URL, optionally performing pre-scrape browser actions or extracting structured JSON using an LLM, to retrieve content in specified formats.

Performs a web search for a query, scrapes content from the top search results using Firecrawl, and returns details in specified formats.

Start an agent job

Tool to start an agent job for agentic web extraction with multi-page navigation and interaction capabilities.

Get team token usage

Tool to retrieve the current team's token usage and balance information for Firecrawl's Extract feature.

Get historical team token usage

Tool to retrieve historical team token usage on a monthly basis.

FRAMEWORKS

How to build Firecrawl MCP Agent with another framework

ChatGPT

Use Firecrawl MCP with ChatGPT

OpenAI Agents SDK

Use Firecrawl MCP with OpenAI Agents SDK

Claude Agent SDK

Use Firecrawl MCP with Claude Agent SDK

Claude Code

Use Firecrawl MCP with Claude Code

Claude Cowork

Use Firecrawl MCP with Claude Cowork

Codex

Use Firecrawl MCP with Codex

Cursor

Use Firecrawl MCP with Cursor

OpenClaw

Use Firecrawl MCP with OpenClaw

Hermes

Use Firecrawl MCP with Hermes

CLI

Use Firecrawl MCP with CLI

Google ADK

Use Firecrawl MCP with Google ADK

LangChain

Use Firecrawl MCP with LangChain

Vercel AI SDK

Use Firecrawl MCP with Vercel AI SDK

Mastra AI

Use Firecrawl MCP with Mastra AI

LlamaIndex

Use Firecrawl MCP with LlamaIndex

CrewAI

Use Firecrawl MCP with CrewAI

OpenCode

Use Firecrawl MCP with OpenCode

VS Code

Use Firecrawl MCP with VS Code

MORE TOOLKITS

Explore Other Toolkits

Toolkit marketplace

Tavily

Api Key

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

Api Key

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

Api Key

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.

Peopledatalabs

Api Key

Peopledatalabs delivers B2B data enrichment and identity resolution APIs. Supercharge your apps with accurate, up-to-date business and contact data.

FAQ

Frequently asked questions

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

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

Start with Firecrawl.It takes 30 seconds.

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

Start building

Customer stories

Teams ship real agents on Composio

GET STARTED FOR FREE BOOK A DEMO

Karan skipped his own birthday party to fix our critical issue. It was 10pm and he diverted his Waymo to help us instead. This really sets the bar — it shows the commitment you need when users rely on your software.

Harsha Gaddipati

Co-founder, Slashy

A lot of students tell us that the moment their connected tools start talking to each other inside Opennote feels almost magical. The agent just knows them, and it's immensely helped keep new users on the platform.

Abhi Arya

Co-founder, Opennote

We chose Composio over Pipedream because it delivered depth where it mattered — niche tools and tricky edge cases other platforms simply ignored. That gave us confidence to scale without compromising.

Nirman Dave

CEO, Zams

As a solo builder, shipping fast is life or death. The only way I can outcompete incumbents is by outmanoeuvring them. Getting bogged down managing agent auth would have been a death sentence.

Ryan Yu

Founder, Extra Thursday

Before Composio, adding tool integrations was slow and resource-intensive. Each one could take weeks of engineering time, and maintaining them meant constantly keeping up with API changes.

Tomisin Jenrola

Founder & CEO, SwarmZero

With hands-on help from their founder, we integrated Gmail and Google Drive in just 30 minutes. This level of personal support and commitment is exactly what startups should strive for.

Jerome Leclanche

Co-Founder, Ingram Technologies

How to integrate Firecrawl MCP with Pydantic AI

Connect Firecrawl without auth hassles

Introduction

Also integrate Firecrawl with

TL;DR

What is Pydantic AI?

What is the Firecrawl MCP server, and what's possible with it?

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

What is Composio SDK?

How the Composio SDK works

Step-by-step Guide

Prerequisites

Getting API Keys for OpenAI and Composio

Install dependencies

Set up environment variables

Import dependencies

Create a Tool Router Session

Initialize the Pydantic AI Agent

Build the chat interface

Run the application

Complete Code

Conclusion

Supported Tools

How to build Firecrawl MCP Agent with another framework

ChatGPT

OpenAI Agents SDK

Claude Agent SDK

Claude Code

Claude Cowork

Codex

Cursor

OpenClaw

Hermes

CLI

Google ADK

LangChain

Vercel AI SDK

Mastra AI

LlamaIndex

CrewAI

OpenCode

VS Code

Explore Other Toolkits

Tavily

Exa

Serpapi

Peopledatalabs

Frequently asked questions

What are the differences in Tool Router MCP and Firecrawl MCP?+

Can I use Tool Router MCP with Pydantic AI?+

Can I manage the permissions and scopes for Firecrawl while using Tool Router?+

How safe is my data with Composio Tool Router?+

Start with Firecrawl.It takes 30 seconds.

Teams ship real agents on Composio