@aigne/example-mcp-server-puppeteer

Puppeteer MCP Server Demo

This is a demonstration of using AIGNE Framework and Puppeteer MCP Server to extract content from websites using Puppeteer.

flowchart LR

in(In)
out(Out)
agent(AI Agent)
puppeteer(Puppeteer MCP Agent)
navigate(Navigate to URL)
evaluate(Evaluate JS)

in --> agent <--> puppeteer

subgraph MCP Agent
  puppeteer <--> navigate
  puppeteer <--> evaluate
end

agent --> out

classDef inputOutput fill:#f9f0ed,stroke:#debbae,stroke-width:2px,color:#b35b39,font-weight:bolder;
classDef processing fill:#F0F4EB,stroke:#C2D7A7,stroke-width:2px,color:#6B8F3C,font-weight:bolder;

class in inputOutput
class out inputOutput
class agent processing
class puppeteer processing
class navigate processing
class evaluate processing

Following is a sequence diagram of the workflow to summarize content from a website:

sequenceDiagram
participant User
participant AI as AI Agent
participant P as Puppeteer MCP Agent
participant N as Navigate to URL
participant E as Evaluate JS

User ->> AI: summarize content from https://www.arcblock.io
AI ->> P: extract content from https://www.arcblock.io
P ->> N: navigate to https://www.arcblock.io
N ->> P: navigation completed
P ->> E: evaluate document.body.innerText
E ->> P: content extracted
E ->> AI: extracted content as context
AI ->> User: The content is as follows: ...

Prerequisites

• Node.js and npm installed on your machine
• OpenAI API key used to interact with OpenAI API
• Pnpm [Optional] if you want to run the example from source code

Try without Installation

export OPENAI_API_KEY=YOUR_OPENAI_API_KEY # setup your OpenAI API key

npx -y @aigne/example-mcp-server-puppeteer # run the example

Installation

Clone the Repository

git clone https://github.com/AIGNE-io/aigne-framework

Install Dependencies

cd aigne-framework/examples/mcp-server-puppeteer

pnpm install

Setup Environment Variables

Setup your OpenAI API key in the .env.local file:

OPENAI_API_KEY="" # setup your OpenAI API key here

Run the Example

pnpm start

Example

The following example demonstrates how to extract content from a website:

import assert from "node:assert";
import { AIAgent, OpenAIChatModel, ExecutionEngine, MCPAgent } from "@aigne/core";

const { OPENAI_API_KEY } = process.env;
assert(OPENAI_API_KEY, "Please set the OPENAI_API_KEY environment variable");

const model = new OpenAIChatModel({
  apiKey: OPENAI_API_KEY,
});

const puppeteerMCPAgent = await MCPAgent.from({
  command: "npx",
  args: ["-y", "@modelcontextprotocol/server-puppeteer"],
});

const engine = new ExecutionEngine({
  model,
  tools: [puppeteerMCPAgent],
});

const agent = AIAgent.from({
  instructions: `\
## Steps to extract content from a website
1. navigate to the url
2. evaluate document.body.innerText to get the content
`,
});

const result = await engine.call(agent, "extract content from https://www.arcblock.io");

console.log(result);
// output:
// {
//   $message: "The content extracted from the website [ArcBlock](https://www.arcblock.io) is as follows:\n\n---\n\n**Redefining Software Architect and Ecosystems**\n\nA total solution for building decentralized applications ...",
// }

await engine.shutdown();

License

This project is licensed under the MIT License.

Changelog

1.3.0 (2025-03-24)

Features

• core: add ChatModelClaude to use models of anthropic (#30) (0a62a64)
• core: add support for subscribing topics for agent memory (#28) (eeecc67)

Bug Fixes

• core: enforce stricter input/output type checks (#26) (ef8cf53)
• rename @aigne/core-next to @aigne/core (3a81009)