How to Use the Firecrawl MCP in CrewAI

Q: How do I stop a runaway Firecrawl job in CrewAI?

Call cancelactivecrawl from your moderator agent. It terminates the task to protect your API credit balance.

Equip your CrewAI agents with web scraping powers. Turn any site into structured context for collaborative research.

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Works with every AI agent you already use

…and any MCP-compatible client

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Connect Firecrawl MCP to CrewAI

Create your Vinkius account to connect Firecrawl to CrewAI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Firecrawl with CrewAI

Ask AI about this MCP

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Claude

Perplexity

Autonomous scraping for CrewAI agents

Assign `scrape_url` to your research agent to convert complex pages into markdown. It allows your agents to parse content without needing a browser engine. The tool handles the JS rendering for you. Your agents receive clean text ready for immediate analysis.

Coordinate bulk crawls in CrewAI

Use `start_crawl` to queue a large-scale data gathering job for your crew. The monitoring agent can track the progress using `get_crawl_status`. This division of labor keeps your research process moving. One agent initiates, while another analyzes the incoming data stream.

Manage budget via CrewAI MCP Server

Check your remaining credits with `get_api_usage` before starting a crawl. It allows your monitor agent to decide if the mission is cost-effective. You can also use `cancel_active_crawl` if your budget hits a threshold. It adds a layer of safety to your autonomous operations.

Setup guide

Set up Firecrawl MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke Firecrawl tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Firecrawl Analyst",
    goal="Access and analyze Firecrawl data via MCP.",
    backstory="Expert analyst with direct Firecrawl access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Firecrawl transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

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

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="Firecrawl Analyst",
        goal="Access and analyze Firecrawl data via MCP.",
        backstory="Expert analyst with direct Firecrawl access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Firecrawl transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

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

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Firecrawl. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

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Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Firecrawl MCP in CrewAI

Yes, assign the scraping tools to your research agents. They can fetch and summarize web data directly into their shared memory.

You can filter tool access so only your research agent can use `scrape_url`. It ensures your CrewAI setup remains organized.

Call `cancel_active_crawl` from your moderator agent. It terminates the task to protect your API credit balance.

Your API key is used strictly for authentication with the service. The server does not log or persist your sensitive keys.

The markdown is returned to the agent's context window. We do not store your retrieved page content on our infrastructure.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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