WayToClawEarn
Beginner45 min readApr 18, 2026

AI Agent Tools 2026 Complete Tutorial: 5 Tools to Build an Automated Pipeline in 30 Minutes

Build AI automation workflow from scratch, OpenClaw + n8n + OpenRouter combination in practice

Beginner · 45 min · Apr 18, 2026

AI Agent tool practical tutorial: from installation to automated workflow

Tutorial Objectives

In 45 minutes, build an automated workflow based on AI Agent from scratch, covering OpenClaw deployment, n8n workflow concatenation, and OpenRouter model access.

What will you build?

  • Local OpenClaw Agent environment (5 minutes to get started quickly)
  • n8n workflow serial AI tool (automated task orchestration)
  • OpenRouter access to multiple models (cost optimization + backup plan)
  • A production-ready AI automated assistant

Preparation list

  • An internet-connected computer (macOS/Linux/Windows)
  • Access to GitHub and npm/yarn -Basic command line experience
  • Curiosity about AI tools

Why choose this combination?

In actual operations, we found that OpenClaw + n8n + OpenRouter is the most cost-effective combination for small and medium-sized teams:

ToolsUsageMonthly Cost
OpenClawAI Agent Scheduling + Task Management$0 (Open Source)
n8nWorkflow automation orchestration$0 (self-hosted)
OpenRouterMulti-model access + cost control$20-50

The advantage of this combination is that OpenClaw is responsible for AI logic and task disassembly, n8n is responsible for external systems and scheduled triggering, and OpenRouter is responsible for calling the most appropriate model on demand.

If you only use OpenAI ChatGPT, the monthly cost may be more than $100. OpenRouter allows you to switch between GPT-4o, Mistral, and Claude, with the cost reduced by 60%.

Step 1: Install OpenClaw (5 minutes)

Basic environment check

terminal

# 检查 Node.js 版本(需要 v18+)
node --version

# 预期输出: v18.x.x 或更高

# 检查 npm
npm --version

# 预期输出: 9.x.x 或更高

安装 OpenClaw

terminal

# 使用 npm 全局安装
npm install -g openclaw

# 验证安装
openclaw --version

初始化配置

terminal

# 创建工作目录
mkdir ai-agent-workspace && cd ai-agent-workspace

# 初始化 OpenClaw
openclaw init

# 按提示配置 API 密钥和默认模型

OpenClaw initialization interface

OpenClaw 会自动创建 SOUL.mdAGENTS.md 等核心文件。如果你用过 Claude Code,会感觉非常亲切——两者都强调"Agent 即服务"的设计理念。

第 2 步:配置 OpenRouter 多模型接入(10 分钟)

为什么需要 OpenRouter

单一模型的问题:

  • GPT-4o 效果好,但成本高($5/1M tokens)
  • Claude 3.5 能力强,但不支持工具调用
  • 遇到服务降级,没有备用方案

OpenRouter 解决了这些问题:统一的 API 接口,按量计费,支持 50+ 模型无缝切换。

获取 OpenRouter API Key

  1. 访问 openrouter.ai
  2. 注册账号并获取 API Key
  3. 充值 $20 起步(支持信用卡)

配置 OpenClaw 使用 OpenRouter

terminal

# 在 OpenClaw 工作目录创建配置文件
cat > openclaw.json << 'EOF'
{
  "model": "openrouter/openai/gpt-4o",
  "fallbacks": [
    "openrouter/mistral/mistral-medium",
    "openrouter/anthropic/claude-3-opus"
  ],
  "api_base": "https://openrouter.ai/api/v1",
  "api_key": "sk-or-v1-your-key-here"
}
EOF

测试多模型切换

terminal

# 测试 GPT-4o
openclaw chat --model openrouter/openai/gpt-4o --prompt "Hello"

# 测试 Claude Opus
openclaw chat --model openrouter/anthropic/claude-3-opus --prompt "Hello"

# 检查成本日志
openclaw cost-log
`__TOK16 __`bash

# 使用 Docker 安装(推荐)
docker run -d \
  --name n8n \
  -p 5678:5678 \
  -v n8n_data:/home/node/.n8n \
  n8nio/n8n

# 或使用 npm
npm install -g n8n
n8n start

创建第一个 AI 工作流

在 n8n 界面中(http://localhost:5678):

  1. 新建 Workflow
  2. 添加 Schedule Trigger(定时触发)
  3. 添加 OpenClaw Node(调用 Agent)
  4. 添加 Telegram/Email Node(通知结果)
json
// OpenClaw Node 配置示例
{
  "model": "openrouter/openai/gpt-4o",
  "prompt": "分析今天的 SEO 热搜,输出前 3 条值得撰写的内容方向",
  "api_base": "https://openrouter.ai/api/v1",
  "api_key": "sk-or-v1-your-key"
}

工作流串联示意

code

## Schedule Trigger
       ↓
[OpenClaw Agent] → 分析 SEO 热词
       ↓
[Condition] → 是否超过阈值?
   Yes → [Email Notification]
   No  → [Log & Skip]

n8n workflow diagram

第 4 步:集成 LangChain 实现高级编排(10 分钟)

为什么需要 LangChain

OpenClaw 负责 Agent 逻辑,n8n 负责任务编排,但如果要做复杂的 RAG(检索增强生成)或 Memory 系统,LangChain 是最好的选择。

基础集成示例

python

# 安装 langchain-openai 和 langchain-community
pip install langchain-openai langchain-community

# 简单的 RAG 流程
from langchain_openai import ChatOpenAI
from langchain_community.retrievers import TavilySearchAPIRetriever

llm = ChatOpenAI(
    model="gpt-4o",
    openai_api_base="https://openrouter.ai/api/v1",
    openai_api_key="sk-or-v1-your-key"
)

# 结合搜索结果生成答案
retriever = TavilySearchAPIRetriever(k=5)
docs = retriever.get_relevant_documents("OpenClaw 最佳实践")
response = llm.invoke(f"基于以下文档回答: {docs}")

与 OpenClaw 联动

LangChain 负责知识检索,OpenClaw 负责任务执行,两者结合可以实现:

  • 实时查询最新数据
  • 基于文档的智能问答
  • 自动生成内容并发布

第 5 步:监控与成本优化(5 分钟)

设置成本告警

在 OpenRouter 仪表盘设置:

  • 月度预算上限:$50
  • 单日花费上限:$5
  • 告警阈值:80%

成本优化策略

策略效果
使用 gpt-4o-mini 替代 gpt-4o成本降 95%,速度升 3 倍
添加 Claude Haiku 作为快速响应模型简单任务平均 $0.001
设置每日前缀预算避免意外超支
terminal

# 查看本周成本
openclaw cost-log --period week

# 查看模型使用分布
openclaw cost-log --model-breakdown

常见问题排查

Q1:OpenClaw 启动报 "Permission denied

terminal

# 修复权限
chmod +x $(which openclaw)

# 或重新安装
npm uninstall -g openclaw && npm install -g openclaw

Q2:OpenRouter API 返回 401

  • 检查 API Key 是否正确
  • 确认账户是否有足够余额
  • 查看 openrouter.ai/keys 状态

Q3:n8n 工作流卡住不动

  • 检查 OpenClaw Agent 是否在运行
  • 查看 n8n 日志:docker logs n8n
  • Confirm that the webhook URL is reachable

Tool entry quick check

ToolsUsageCost
OpenClawAI Agent SchedulingOpen Source and Free
n8nWorkflow automationOpen source and free
OpenRouterMulti-model access$0.5-5/1M tokens
LangChainRAG + Knowledge BaseOpen Source and Free
Claude CodeCode writing assistance$3-15/1M tokens

Next action

  1. Complete the above 5-step installation
  2. Run your first automated workflow
  3. Monitor costs for a week and optimize model selection
  4. Integrate this process into your content publishing system

If you encounter problems, please leave a message at waytoclawearn.com and I will update the FAQ section.


Related Tools: OpenClaw, n8n, OpenRouter, LangChain, Claude Code

Disclaimer: this site shares educational insights only, for inspiration and reference. No outcome guarantee; external execution and decisions are your own responsibility.

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