Firecrawl Deep Research

Connect AI agents to Firecrawl Deep Research for comprehensive web-based research and analysis

Prerequisites Before you begin, create an account and get your API Key.

Getting started

Connect to Firecrawl Deep Research to perform comprehensive web-based research, analysis, and in-depth topic exploration through AI agents.

API

1. Install the SDKs (optional)

   pip

   pip install klavis
   
2. Create a Strata MCP Server with Firecrawl Deep Research

   Python

   from klavis import Klavis
   from klavis.types import McpServerName
   
   klavis_client = Klavis(api_key="YOUR_API_KEY")
   
   # Create a Strata MCP server with Firecrawl Deep Research
   response = klavis_client.mcp_server.create_strata_server(
       servers=[McpServerName.FIRECRAWL_DEEP_RESEARCH],
       user_id="user123"
   )
   

   userId specifies whose connected accounts and data you are accessing in Klavis. It should be a unique id for yourself, your team, or your organization.

   API Reference

   Full Strata API endpoints

3. Authenticate with API Key

   You can get your Firecrawl API key from the Firecrawl website.

   Python

   klavis_client.mcp_server.set_strata_auth(
       strata_id=response.strata_id,
       server_name=McpServerName.FIRECRAWL_DEEP_RESEARCH,
       auth_data={
           "api_key": "YOUR_FIRECRAWL_API_KEY"
       }
   )
   

   🎉 Your Firecrawl Deep Research MCP Server is ready! Once authentication is complete, you can use your MCP server URL with any MCP-compatible client.

UI

1. Open Dashboard

   Go to your Dashboard.

2. Choose Firecrawl Deep Research

   Select Firecrawl Deep Research from the list of available integrations.

3. Configure API Key

   Enter your Firecrawl API key to enable research functionality.

4. Use in your app

   Copy the MCP endpoint URL and add it to your MCP-supported client (Claude Desktop, Cursor, VS Code, etc.).

Open Source

1. Clone repository (for developers to build from source)

   git clone https://github.com/klavis-ai/klavis
   cd klavis/mcp_servers/firecrawl_deep_research
   
2. Run with Docker

   # Pull the Docker image
   docker pull ghcr.io/klavis-ai/firecrawl-deep-research-mcp-server:latest
   
   # Run with API key support (requires Klavis API key)
   docker run -p 5000:5000 \
     -e KLAVIS_API_KEY=$KLAVIS_API_KEY \
     ghcr.io/klavis-ai/firecrawl-deep-research-mcp-server:latest
   
3. Configure MCP client

   {
     "mcpServers": {
       "firecrawl_deep": {
         "url": "http://localhost:5000/mcp/"
       }
     }
   }
   

Available Tools

With our progressive discovery approach, Klavis System is capable of enabling all tools for Firecrawl Deep Research. Please use the get_tools API for more details. If you find any tool that is missing, please reach out to [e-mail].

Next Steps

AI Platform Integrations

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Integrations

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API Reference

REST endpoints and schemas

White-label Authentication

Customize OAuth flows with your own branding