Firecrawl MCP Server for Pydantic AI 4 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Firecrawl through the Vinkius and every tool is automatically validated against Pydantic schemas — catch errors at build time, not in production.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP
async def main():
# Your Vinkius token — get it at cloud.vinkius.com
server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
agent = Agent(
model="openai:gpt-4o",
mcp_servers=[server],
system_prompt=(
"You are an assistant with access to Firecrawl "
"(4 tools)."
),
)
result = await agent.run(
"What tools are available in Firecrawl?"
)
print(result.data)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Firecrawl MCP Server
Connect your AI agent to Firecrawl — the most popular web scraping API built specifically for AI and LLM applications.
Pydantic AI validates every Firecrawl tool response against typed schemas, catching data inconsistencies at build time. Connect 4 tools through the Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code — full type safety, structured output guarantees, and dependency injection for testable agents.
What you can do
- Scrape Pages — Extract clean Markdown from any URL. Firecrawl handles JavaScript rendering, anti-bot protection, cookie banners, and dynamic content automatically
- Search the Web — Search and scrape in one call. Get Google-like search results with full page content already extracted
- Crawl Websites — Recursively crawl entire sites, following internal links. Perfect for indexing documentation, blogs, or product catalogs
- Map Sites — Discover all URLs on a domain without scraping content. Understand site structure before deciding what to extract
The Firecrawl MCP Server exposes 4 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Firecrawl to Pydantic AI via MCP
Follow these steps to integrate the Firecrawl MCP Server with Pydantic AI.
Install Pydantic AI
Run pip install pydantic-ai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 4 tools from Firecrawl with type-safe schemas
Why Use Pydantic AI with the Firecrawl MCP Server
Pydantic AI provides unique advantages when paired with Firecrawl through the Model Context Protocol.
Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application
Model-agnostic architecture — switch between OpenAI, Anthropic, or Gemini without changing your Firecrawl integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Firecrawl connection logic from agent behavior for testable, maintainable code
Firecrawl + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Firecrawl MCP Server delivers measurable value.
Type-safe data pipelines: query Firecrawl with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Firecrawl tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Firecrawl and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Firecrawl responses and write comprehensive agent tests
Firecrawl MCP Tools for Pydantic AI (4)
These 4 tools become available when you connect Firecrawl to Pydantic AI via MCP:
crawl_site
Each page is scraped and converted to Markdown. Returns a job ID to track progress. Crawl an entire website and extract content from multiple pages. Returns a job ID for async tracking
map_site
Useful for understanding site architecture before deciding which pages to scrape. Discover all URLs on a website without scraping content. Returns a sitemap of discovered links
scrape_page
Handles anti-bot protection, cookie banners, and dynamic content automatically. Scrape a single web page and extract its content as clean Markdown. Perfect for reading articles, documentation, and product pages
search_web
Ideal for research, fact-checking, and gathering information on any topic. Search the web and return scraped content from the top results. Combines Google-like search with automatic content extraction
Example Prompts for Firecrawl in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Firecrawl immediately.
"Scrape the main page of docs.firecrawl.dev and give me a summary of what Firecrawl offers."
"Search the web for 'best practices for RAG pipelines 2026' and return the top 3 results with content."
"Map all pages on example.com to see the site structure."
Troubleshooting Firecrawl MCP Server with Pydantic AI
Common issues when connecting Firecrawl to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiFirecrawl + Pydantic AI FAQ
Common questions about integrating Firecrawl MCP Server with Pydantic AI.
How does Pydantic AI discover MCP tools?
MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.Does Pydantic AI validate MCP tool responses?
Can I switch LLM providers without changing MCP code?
Connect Firecrawl with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Firecrawl to Pydantic AI
Get your token, paste the configuration, and start using 4 tools in under 2 minutes. No API key management needed.