Firecrawl n8n Integration

Install and configure the official Firecrawl nodes for n8n to scrape, crawl, map, search, and extract data from websites. Turn entire websites into LLM-ready markdown or structured data with a single API.

What This Skill Does

This skill guides you through installing and configuring the `@mendable/n8n-nodes-firecrawl` community package in n8n, enabling you to:

Prerequisites

Installation Instructions

Step 1: Install the Firecrawl Community Node

1. In your n8n instance, navigate to **Settings** → **Community Nodes**

2. Click **Install a community node**

3. Enter the package name: `@mendable/n8n-nodes-firecrawl`

4. Click **Install**

5. Wait for installation to complete

**For Docker/self-hosted installations:**

```yaml

version: '3'

services:

n8n:

image: n8nio/n8n

environment:

- N8N_COMMUNITY_PACKAGES_ALLOW_TOOL_USAGE=true

ports:

- "5678:5678"

volumes:

- ~/.n8n:/home/node/.n8n

```

Set the environment variable `N8N_COMMUNITY_PACKAGES_ALLOW_TOOL_USAGE=true` to enable AI tool usage.

Step 2: Configure Firecrawl Credentials

1. In your n8n workflow, add a **Firecrawl** node

2. When prompted for credentials, click **Create New Credentials**

3. Enter your Firecrawl API key (obtain from https://firecrawl.dev dashboard)

4. Save the credentials

**Security Note:** Keep your API key secure and never commit it to version control.

Step 3: Choose Your Operation

The Firecrawl node supports the following operations:

#### Core Operations

#### Batch Operations

#### Management Operations

#### Usage Tracking

Step 4: Configure Operation Parameters

Each operation has specific parameters. Common configurations:

**For Scrape operation:**

**For Crawl operation:**

**For Map operation:**

**For Extract Data operation:**

Step 5: Using with AI Agents (Optional)

To use Firecrawl as a tool for AI agents:

1. Add an **AI Agent** node to your workflow

2. Connect the **Firecrawl** node as a tool input to the AI Agent node

3. The AI agent will automatically decide when to use Firecrawl operations

**Dynamic Parameter Definition:**

Use the `$fromAI()` function to let the AI agent decide parameter values:

```javascript

// Let AI decide the URL to scrape

{{ $fromAI("url", "The URL to scrape", "string") }}

// Let AI decide the search query

{{ $fromAI("query", "Search query for finding relevant pages", "string") }}

// Let AI decide whether to include subdomains

{{ $fromAI("includeSubdomains", "Whether to include subdomains", "boolean", false) }}

```

Click the **"Let the model define this parameter"** button next to any field to enable this feature.

Step 6: Test Your Workflow

1. Click **Execute Node** to test the Firecrawl operation

2. Review the output in the node's output panel

3. Verify the data format matches your expectations

4. Adjust parameters as needed

Best Practices

1. **Start with Map**: For unknown websites, use the Map operation first to discover available URLs

2. **Set reasonable limits**: Configure crawl depth and page limits to prevent excessive API usage

3. **Use Include/Exclude patterns**: Filter URLs efficiently with path patterns instead of crawling everything

4. **Handle errors gracefully**: Add error handling nodes to manage failed scrapes or crawls

5. **Monitor usage**: Regularly check your token and credit usage with the tracking operations

6. **Cache results**: Store scraped data to avoid re-scraping the same content

7. **Use batch operations**: For multiple URLs, use Batch Scrape instead of individual scrape operations

8. **Provide clear prompts**: When using Extract, write specific prompts and schemas for better AI extraction

AI Agent Best Practices

1. **Use clear operation names**: AI agents rely on operation descriptions to make decisions

2. **Provide context in prompts**: Give the agent clear instructions on what data to extract

3. **Set default limits**: Configure sensible defaults to prevent runaway API costs

4. **Chain operations**: Use Map → Scrape/Crawl workflows for better results

5. **Test incrementally**: Start with small limits when testing AI agent integrations

Example Use Cases

Troubleshooting

Additional Resources

Important Notes