How does Firecrawl pricing work?

Firecrawl uses a credit-based system. You get 500 free lifetime credits to start (no credit card required). Base cost is 1 credit per page scraped. Advanced features like JSON extraction (+4 credits) or enhanced mode (+4 credits) consume additional credits per page. Paid plans start at $16/month with 3,000 monthly credits.

Can Firecrawl handle JavaScript-heavy websites?

Yes! Firecrawl renders pages in a full browser environment before extracting content — this means it handles React, Next.js, Angular, and any other JavaScript framework. It also automatically bypasses common anti-bot protections, removes cookie consent banners, and waits for dynamic content to load before extraction.

What formats does Firecrawl return?

Firecrawl can return content in multiple formats: Markdown (default and most popular for LLM consumption), HTML, raw HTML, structured JSON (with LLM-powered extraction), screenshots, links, and page metadata. You can request multiple formats in a single call.

Firecrawl MCP Server for CrewAI 4 tools — connect in under 2 minutes

Name: Firecrawl
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 4 Tools Framework

Connect your CrewAI agents to Firecrawl through Vinkius, pass the Edge URL in the `mcps` parameter and every Firecrawl tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

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Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Firecrawl Specialist",
    goal="Help users interact with Firecrawl effectively",
    backstory=(
        "You are an expert at leveraging Firecrawl tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Firecrawl "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 4 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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* 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.

When paired with CrewAI, Firecrawl becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Firecrawl tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

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 CrewAI 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 CrewAI via MCP

Follow these steps to integrate the Firecrawl MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 4 tools from Firecrawl

Why Use CrewAI with the Firecrawl MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Firecrawl through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Firecrawl + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Firecrawl MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Firecrawl for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Firecrawl, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Firecrawl tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Firecrawl against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Firecrawl MCP Tools for CrewAI (4)

These 4 tools become available when you connect Firecrawl to CrewAI 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 CrewAI

Ready-to-use prompts you can give your CrewAI 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 CrewAI

Common issues when connecting Firecrawl to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Firecrawl + CrewAI FAQ

Common questions about integrating Firecrawl MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.