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Prerequisites

To get the most out of this guide, you’ll need to:

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1. Create a Firecrawl Web Search MCP Server

Use the following endpoint to create a new remote Firecrawl Web Search MCP server instance:

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Request

curl --request POST \
  --url https://api.klavis.ai/mcp-server/instance/create \
  --header 'Authorization: Bearer <YOUR_API_KEY>' \
  --header 'Content-Type: application/json' \
  --data '{
  "serverName": "Firecrawl Web Search",
  "userId": "<YOUR_USER_ID>",
  "platformName": "<YOUR_PLATFORM_NAME>"
}'

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Response

{
  "serverUrl": "https://firecrawl-websearch-mcp-server.klavis.ai/sse?instance_id=<instance-id>",
  "instanceId": "<instance-id>"
}
serverUrl specifies the endpoint of the Firecrawl Web Search MCP server, which allows you to perform real-time web searches.
instanceId is used for authentication and identification of your server instance.

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2. Configure Firecrawl API Key

To use the Firecrawl Deep Research MCP Server, you need to configure it with your Firecrawl API key.

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Setting up Firecrawl API Key

curl --request POST \
  --url https://api.klavis.ai/mcp-server/instance/set-auth-token \
  --header 'Authorization: Bearer <YOUR_KLAVIS_API_KEY>' \
  --header 'Content-Type: application/json' \
  --data '{
  "instanceId": "<YOUR_INSTANCE_ID>",
  "authToken": "<YOUR_FIRECRAWL_API_KEY>"
}'

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Response

{
  "success": true,
  "message": "<string>"
}

​
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