FI

firecrawl-deploy-integration

Automates the deployment of Firecrawl-powered web scraping applications to cloud platforms including Vercel and Google Cloud Run.

Install

mkdir -p .claude/skills/firecrawl-deploy-integration && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/5420" && unzip -o skill.zip -d .claude/skills/firecrawl-deploy-integration && rm skill.zip

Installs to .claude/skills/firecrawl-deploy-integration

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

Deploy Firecrawl integrations to Vercel, Cloud Run, and Docker platforms.
73 charsno explicit “when” trigger
Intermediate

Key capabilities

  • →Configure Vercel environment variables for Firecrawl API keys
  • →Deploy self-hosted Firecrawl applications using Docker Compose
  • →Set up Cloud Run services with Firecrawl API key secrets
  • →Establish webhook endpoints for asynchronous crawl results
  • →Implement health checks for Firecrawl applications

How it works

The skill configures platform-specific secrets and deployment settings for Vercel, Cloud Run, or Docker. It provides code examples for serverless API routes, Docker Compose, and webhook handling.

Inputs & outputs

You give it
Firecrawl API key, application code, and deployment platform choice
You get back
Deployed Firecrawl application on Vercel, Cloud Run, or Docker

When to use firecrawl-deploy-integration

  • →Configure Vercel environment variables
  • →Deploy self-hosted Firecrawl via Docker
  • →Set up Cloud Run secret management
  • →Establish deployment pipelines for scraping tools

About this skill

Firecrawl Production Deployment

Overview

Deploy the application client and the Firecrawl service as separate responsibilities. Cloud integrations need a protected key and egress policy; self-hosting adds databases, queues, browsers, storage, authentication, upgrades, and recovery.

Prerequisites

  • The target repository or integration path and the requested operator outcome.
  • The source authorization, data classification, and environment policy.
  • Current Firecrawl documentation, credentials only when needed, and an owner for approvals.

Current Contract

Cloud clients use the v2 API and secret-managed FIRECRAWL_API_KEY. The official self-host guide's Compose example is an evaluation baseline with authentication disabled and without durable storage, TLS, high availability, or every Cloud capability. Pin the reviewed release and its own Compose contract; do not copy a floating main configuration into production.

Authentication

For authenticated Cloud operations, inject FIRECRAWL_API_KEY from an approved secret manager. REST requests use Authorization: Bearer with the key. Never print, commit, transmit, or place a key in a URL. Keyless access is suitable only where the current documentation explicitly allows it and the workload accepts its limits; production workflows should make identity and team ownership explicit.

Instructions

  1. Inventory the application release, Firecrawl Cloud or self-host decision, required features, environments, domains, data flows, SLOs, and rollback owner.
  2. For Cloud, inject the key from the platform secret manager, restrict outbound destinations, choose retention/cache policy, and prevent request or response bodies from application logs.
  3. For self-hosting, pin a verified release and review its Compose, SELF_HOST, and feature-support documentation. Map every optional provider and outbound flow.
  4. Before exposure, add supported authentication, network controls, TLS, durable PostgreSQL/Redis/RabbitMQ storage where required, backups, restore tests, monitoring, capacity limits, and upgrade rollback.
  5. Deploy a no-traffic revision, verify process readiness separately from one approved functional v2 scrape, then run a bounded content-free canary.
  6. Observe errors, queue pressure, latency, credit or capacity use, and output-quality metrics. Promote gradually with explicit stop thresholds.
  7. Record the release/image digest, configuration hashes, canary evidence, approvals, and rollback result.

Tool Discipline

Use Read, Glob, and Grep to inspect code, configuration, tests, and evidence. Use Write/Edit only for approved implementation or documentation changes. Do not call Firecrawl, rotate keys, change account settings, scrape a target, or deploy merely because this skill was invoked.

Approval Boundaries

Require approval before exposing a self-hosted API, disabling authentication, adding external AI/proxy providers, granting production secrets, changing retention, or increasing rollout traffic.

Output

Return deployment topology, immutable versions, secret and network controls, storage/recovery posture, capability gaps, readiness and functional canary results, rollout state, and tested rollback command or procedure.

Error Handling

  • Readiness passes but scrape fails: inspect API and browser-service evidence; do not declare the deployment healthy.
  • Self-hosted capability is absent: stop and choose Cloud or validate its external dependency.
  • Rollback cannot restore data/configuration: block production promotion.

Examples

  • "Deploy our Firecrawl client" produces a secret-managed canary rollout and rollback receipt.
  • "Expose the quickstart Compose file publicly" is blocked until production authentication, TLS, storage, and recovery exist.

Resources

Read official Firecrawl evidence before relying on an endpoint, SDK method, plan limit, price, retention option, or self-hosted release.

When not to use it

  • →When the scrape takes longer than 10 seconds on Vercel
  • →When the application requires more than 512MiB memory on Cloud Run
  • →When the webhook URL is not publicly accessible

Prerequisites

Firecrawl API key (FIRECRAWL_API_KEY)Application using @mendable/firecrawl-jsPlatform CLI (vercel, docker, or gcloud)

Limitations

  • →Vercel deployments may timeout if scrapes exceed 10 seconds
  • →Self-hosted Docker instances may run out of memory with Playwright browser
  • →Cloud Run deployments can experience cold starts

How it compares

This skill automates the setup of Firecrawl deployments across various platforms, unlike manual configuration which requires platform-specific knowledge for each environment.

Compared to similar skills

firecrawl-deploy-integration side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
firecrawl-deploy-integration (this skill)12moReviewIntermediate
evernote-deploy-integration02moReviewIntermediate
exa-deploy-integration02moReviewAdvanced
azure-partner-solutions06moNo flagsAdvanced

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