How to Use the Firecrawl MCP in AutoGen

Q: How do I limit credit usage in AutoGen with Firecrawl?

You can assign a specific agent to check getapiusage before any crawl. The agent can block further calls to startcrawl if the remaining credit balance is too low.

Let your AutoGen agents debate, map, and scrape web data using the Firecrawl MCP Server.

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Connect Firecrawl MCP to AutoGen

Create your Vinkius account to connect Firecrawl to AutoGen 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 AutoGen

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Multi-agent web scraping debates using AutoGen

AutoGen excels at letting specialized agents coordinate. You can set up a research agent that requests a crawl using `start_crawl`, while a separate budget agent constantly calls `get_api_usage` to ensure the scrape doesn't exceed your credit limits. If the budget agent detects that a deep crawl is too expensive, it can instruct the coordinator to call `cancel_active_crawl`. This cooperative loop ensures your automated web research stays within financial guardrails.

Map site structures before executing scrapes

Instead of blindly scraping every page, your AutoGen planner agent can call `map_website_structure` to analyze a target domain. It then presents the URL map to a filtering agent, which selects only high-value pages for extraction. Once the target list is refined, the agent calls `scrape_url` on those specific paths. This targeted approach avoids wasting resources on privacy pages, terms of service, or duplicate content.

Verify crawl status across agent conversations

When running large asynchronous crawls, your AutoGen agents don't have to sit idle. The scraping agent can trigger `start_crawl` and pass the job ID to a monitoring agent, while other agents continue analyzing previously fetched data. The monitoring agent calls `get_crawl_status` at set intervals. Once the crawl is complete, it alerts the group, allowing the analyzer agents to process the newly delivered markdown.

Setup guide

Set up Firecrawl MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Firecrawl tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

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

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Firecrawl_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Firecrawl data")
print(result.messages[-1].content)

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Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

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

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Firecrawl_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Firecrawl data")
    print(result.messages[-1].content)

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.

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Common questions about Firecrawl MCP in AutoGen

You register the server using the AutoGen MCP extension. The tools, including `scrape_url` and `start_crawl`, are automatically mapped to schemas your agents can call during their conversations.

Yes, if one agent notices a crawl is taking too long by checking `get_crawl_status`, it can message the operator agent to execute `cancel_active_crawl` immediately.

You can assign a specific agent to check `get_api_usage` before any crawl. The agent can block further calls to `start_crawl` if the remaining credit balance is too low.

Yes, the server handles modern single-page applications and JS rendering. When your agent calls `scrape_url`, it receives the rendered page converted into markdown.

All scraped markdown, raw HTML, and URL lists processed by this server run through secure, isolated sandboxes. No scraped data is cached or stored permanently on the host platform.

Use it with your favorite AI tools

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

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