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open-agent-builder

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由 Firecrawl 驱动的 AI 智能体可视化工作流构建器——支持拖放式网页抓取管道,并实时执行。

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工具介绍

由 Firecrawl 驱动的 AI 智能体可视化工作流构建器——支持拖放式网页抓取管道,并实时执行。

Open Agent Builder


What is Open Agent Builder?

Open Agent Builder is a visual workflow builder for creating AI agent pipelines powered by Firecrawl. Design complex agent workflows with a drag-and-drop interface, then execute them with real-time streaming updates.

Perfect for:

  • Web scraping and data extraction workflows
  • Multi-step AI agent pipelines
  • Automated research and content generation
  • Data transformation and analysis
  • Web automation with human-in-the-loop approvals

Note: This project is actively under development. Some features are still in progress and we welcome contributions and PRs!


Key Features

Visual Workflow Builder

  • Drag-and-drop interface for building agent workflows
  • Real-time execution with streaming updates
  • 8 core node types: Start, Agent, MCP Tools, Transform, If/Else, While Loop, User Approval, End
  • Template library with pre-built workflows
  • MCP protocol support for extensible tool integration

Powered by Firecrawl

  • Native Firecrawl integration for web scraping and searching

Enterprise Features

  • LangGraph execution engine for reliable state management
  • Clerk authentication for secure multi-user access
  • Convex database for persistent storage
  • API endpoints for programmatic execution
  • Human-in-the-loop approvals for sensitive operations

Tech Stack

Technology Purpose
Firecrawl Web scraping API for converting websites into LLM-ready data
Next.js 16 (canary) React framework with App Router for frontend and API routes
TypeScript Type-safe development across the stack
LangGraph Workflow orchestration engine with state management, conditional routing, and human-in-the-loop support
Convex Real-time database with automatic reactivity for workflows, executions, and user data
Clerk Authentication and user management with JWT integration
Tailwind CSS Utility-first CSS framework for responsive UI
React Flow Visual workflow builder canvas with drag-and-drop nodes
Anthropic Claude AI integration with native MCP support (Claude Haiku 4.5 & Sonnet 4.5)
OpenAI gpt-5 integration (MCP support coming soon)
Groq Fast inference for open models (MCP support coming soon)
E2B Sandboxed code execution for secure transform nodes
Vercel Deployment platform with edge functions

Prerequisites

Before you begin, you'll need:

  1. Node.js 18+ installed on your machine
  2. Firecrawl API key (Required for web scraping) - Get one here
  3. Convex account - Sign up free
  4. Clerk account - Sign up free

Note: LLM API keys can be added directly in the UI via Settings → API Keys after setup. For MCP tool support, Anthropic Claude (Haiku 4.5 or Sonnet 4.5) is currently recommended as the default option.


Installation & Setup

1. Clone the Repository

bash
git clone https://github.com/firecrawl/open-agent-builder.git
cd open-agent-builder
npm install

2. Set Up Convex (Database)

Convex handles all workflow and execution data persistence.

bash
# Install Convex CLI globally
npm install -g convex

# Initialize Convex project
npx convex dev

This will:

  • Open your browser to create/link a Convex project
  • Generate a NEXT_PUBLIC_CONVEX_URL in your .env.local
  • Start the Convex development server

Keep the Convex dev server running in a separate terminal.

3. Set Up Clerk (Authentication)

Clerk provides secure user authentication and management.

  1. Go to clerk.com and create a new application
  2. In your Clerk dashboard:
    • Go to API Keys
    • Copy your keys
  3. Go to JWT Templates → Convex:
    • Click "Apply"
    • Copy the issuer URL

Add to your .env.local:

bash
# Clerk Authentication
NEXT_PUBLIC_CLERK_PUBLISHABLE_KEY=pk_test_...
CLERK_SECRET_KEY=sk_test_...

# Clerk + Convex Integration
CLERK_JWT_ISSUER_DOMAIN=https://your-clerk-domain.clerk.accounts.dev

4. Configure Convex Authentication

Edit convex/auth.config.ts and update the domain:

typescript
export default {
  providers: [
    {
      domain: "https://your-clerk-domain.clerk.accounts.dev", // Your Clerk issuer URL
      applicationID: "convex",
    },
  ],
};

Then push the auth config to Convex:

bash
npx convex dev

5. Set Up Firecrawl (Required)

Firecrawl is the core web scraping engine that powers most workflows.

  1. Get your API key at firecrawl.dev
  2. Add to .env.local:
bash
# Firecrawl API (REQUIRED)
FIRECRAWL_API_KEY=fc-...

Note: Users can also add their own Firecrawl keys in Settings → API Keys, but having a default key in .env.local enables the template workflows.

6. Optional: Configure Default LLM Provider

While users can add their own LLM API keys through the UI (Settings → API Keys), you can optionally set a default provider in .env.local:

bash
# Optional: Choose one as default

# Anthropic Claude (Recommended - Native MCP support with Haiku 4.5 & Sonnet 4.5)
ANTHROPIC_API_KEY=sk-ant-...

# OpenAI GPT-5 (MCP support coming soon)
OPENAI_API_KEY=sk-...

# Groq (MCP support coming soon)
GROQ_API_KEY=gsk_...

Important: For workflows using MCP tools (like Firecrawl integration), Anthropic Claude is currently the recommended provider as it has native MCP support. OpenAI and Groq MCP support is coming soon.

7. Optional: E2B Code Interpreter

For advanced transform nodes with sandboxed code execution:

bash
# E2B Code Interpreter (Optional)
E2B_API_KEY=e2b_...

Get your key at e2b.dev


Running the Application

Development Mode

bash
# Terminal 1: Convex dev server
npx convex dev

# Terminal 2: Next.js dev server
npm run dev

Or run both with one command:

bash
npm run dev:all

Visit http://localhost:3000

Production Build

bash
npm run build
npm start

Quick Start Guide

Your First Workflow

  1. Sign Up/Login at http://localhost:3000
  2. Add your LLM API key in Settings → API Keys
    • For MCP tool support: Use Anthropic Claude (Haiku 4.5 or Sonnet 4.5)
    • For basic workflows: OpenAI or Groq also work
  3. Click "New Workflow" or select a template
  4. Try the "Simple Web Scraper" template:
    • Pre-configured to scrape any website
    • Uses Firecrawl for extraction
    • AI agent summarizes the content
  5. Click "Run" and enter a URL
  6. Watch real-time execution with streaming updates

Understanding Node Types

Node Type Purpose Example Use
Start Workflow entry point Define input variables
Agent AI reasoning with LLMs Analyze data, make decisions
MCP Tool External tool calls Firecrawl scraping, APIs
Transform Data manipulation Parse JSON, filter arrays
If/Else Conditional logic Route based on conditions
While Loop Iteration Process multiple pages
User Approval Human-in-the-loop Review before posting
End Workflow completion Return final output

MCP Tool Support

Current Support

Anthropic Claude - Full native MCP support

  • Claude Sonnet 4.5 (Recommended)
  • Claude Haiku 4.5

Anthropic's MCP implementation provides MCP support, other providers are currently in progress.

Coming Soon

  • OpenAI - MCP support in development
  • Gemini - MCP support in development
  • Open Router - coming soon...

Using MCP Tools

MCP tools enable agents to interact with external services like Firecrawl:

  1. Add an Agent node to your workflow
  2. In the node settings, select MCP Tools
  3. Choose Firecrawl or add a custom MCP server
  4. The agent can now call Firecrawl tools like scrape, search, crawl

Example workflow with MCP:

Start → Agent (with Firecrawl MCP) → End

The agent can intelligently decide when to scrape pages, search the web, or crawl sites based on your instructions.


Example Workflows

1. Simple Web Scraper

What it does: Scrape any website and get an AI summary

Nodes: Start → Firecrawl Scrape → Agent Summary → End

Try it:

bash
Input: https://firecrawl.dev
Output: "Firecrawl is a web scraping API that converts websites into LLM-ready markdown..."

2. Multi-Page Research

What it does: Search web, scrape top results, synthesize findings

Nodes: Start → Firecrawl Search → Loop (Scrape Each) → Agent Synthesis → End

3. Competitive Analysis

What it does: Research companies, extract structured data, generate report

Nodes: Start → Parse Companies → Loop (Research + Extract) → Approval → Export → End

Features used:

  • Firecrawl web search
  • Structured JSON extraction
  • While loops for iteration
  • Human approval gates
  • Conditional routing

4. Price Monitoring

What it does: Track product prices across multiple sites

Nodes: Start → Loop (Scrape + Extract Price) → Compare → Notify → End


Configuration

User-Level API Keys

Users can add their own API keys via Settings → API Keys:

  • LLM Providers: Anthropic (Recommended for MCP), OpenAI, Groq (Required - add at least one)
  • Firecrawl: Personal API key (Optional - falls back to environment variable)
  • Custom MCP Servers: Authentication tokens

This allows:

  • Each user to use their own API quotas
  • Fallback to environment variables if not set
  • Easy key rotation and management

MCP Server Registry

Add custom MCP servers in Settings → MCP Registry:

  1. Click "Add MCP Server"
  2. Enter server URL and authentication
  3. Test connection to discover available tools
  4. Use in Agent nodes by selecting from MCP tools dropdown

Supported MCP Servers:

  • Firecrawl (built-in)
  • Custom HTTP endpoints
  • Environment variable substitution: {API_KEY}

Deployment

Deploying to Vercel

  1. Push your code to GitHub

  2. Deploy to Vercel:

    bash
    # Install Vercel CLI
    npm i -g vercel
    
    # Deploy
    vercel
  3. Set environment variables in Vercel dashboard:

    • NEXT_PUBLIC_CONVEX_URL (from Convex)
    • Clerk keys
    • FIRECRAWL_API_KEY (Required)
    • Optional: Default LLM provider keys
  4. Deploy Convex to production:

    bash
    npx convex deploy
  5. Update Clerk settings:

    • Add your Vercel domain to allowed origins
    • Update redirect URLs

Environment Variables Checklist

Required:

  • NEXT_PUBLIC_CONVEX_URL - Convex database
  • NEXT_PUBLIC_CLERK_PUBLISHABLE_KEY - Clerk auth
  • CLERK_SECRET_KEY - Clerk auth
  • CLERK_JWT_ISSUER_DOMAIN - Clerk + Convex integration
  • FIRECRAWL_API_KEY - Web scraping

Optional (can be added in UI instead):

  • ANTHROPIC_API_KEY - Default Claude provider (Recommended for MCP)
  • OPENAI_API_KEY - Default gpt-5 provider (MCP coming soon)
  • GROQ_API_KEY - Default Groq provider (MCP coming soon)
  • E2B_API_KEY - Sandboxed code execution

API Usage

Programmatic Execution

Generate an API key in Settings → API Keys, then:

bash
curl -X POST https://your-domain.com/api/workflows/my-workflow-id/execute-stream \
  -H "Authorization: Bearer sk_live_..." \
  -H "Content-Type: application/json" \
  -d '{"url": "https://example.com"}'

Response: Server-Sent Events (SSE) stream with real-time updates

Architecture

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> 工具信息

发布日期2026年8月1日
最后更新2026年9月17日
分类编程语言
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