Add Skim to your agent in 30 seconds

{
  "type": "function",
  "function": {
    "name": "skim_read_url",
    "description": "Fetch any web page and return clean, readable Markdown plus structured metadata (title, author, byline, site name, published date). Use this whenever the user asks you to read, summarize, quote from, or analyze a URL. Strips ads, navigation, scripts, and tracking. Each call costs $0.002 in USDC and is paid automatically over x402.",
    "parameters": {
      "type": "object",
      "properties": {
        "url": {
          "type": "string",
          "description": "Absolute https URL of the page to read."
        }
      },
      "required": ["url"],
      "additionalProperties": false
    }
  }
}

{
  "name": "skim_read_url",
  "description": "Fetch any web page and return clean, readable Markdown plus structured metadata (title, author, byline, site name, published date). Use this whenever the user asks you to read, summarize, quote from, or analyze a URL. Strips ads, navigation, scripts, and tracking. Each call costs $0.002 in USDC and is paid automatically over x402.",
  "input_schema": {
    "type": "object",
    "properties": {
      "url": {
        "type": "string",
        "description": "Absolute https URL of the page to read."
      }
    },
    "required": ["url"]
  }
}

{
  "function_declarations": [
    {
      "name": "skim_read_url",
      "description": "Fetch any web page and return clean, readable Markdown plus structured metadata. Strips ads, navigation, scripts, and trackers. Each call costs $0.002 in USDC, paid automatically over x402.",
      "parameters": {
        "type": "OBJECT",
        "properties": {
          "url": {
            "type": "STRING",
            "description": "Absolute https URL of the page to read."
          }
        },
        "required": ["url"]
      }
    }
  ]
}

import { tool } from "ai";
import { z } from "zod";
import { createWalletClient, http } from "viem";
import { privateKeyToAccount } from "viem/accounts";
import { base } from "viem/chains";
import { wrapFetchWithPayment } from "x402-fetch";

const account = privateKeyToAccount(process.env.WALLET_PRIVATE_KEY as `0x${string}`);
const wallet = createWalletClient({ account, transport: http(), chain: base });
const fetchWithPayment = wrapFetchWithPayment(fetch, wallet);

export const skimReadUrl = tool({
  description:
    "Fetch any web page and return clean Markdown plus metadata. " +
    "Strips ads, navigation, and trackers. " +
    "Costs $0.002 in USDC, paid automatically over x402.",
  parameters: z.object({
    url: z.string().url().describe("Absolute https URL of the page to read."),
  }),
  execute: async ({ url }) => {
    const res = await fetchWithPayment("https://skim402.com/api/v1/read", {
      method: "POST",
      headers: { "Content-Type": "application/json" },
      body: JSON.stringify({ url }),
    });
    if (!res.ok) throw new Error(`Skim ${res.status}: ${await res.text()}`);
    return await res.json();
  },
});

from langchain_core.tools import tool
from x402 import x402ClientSync
from x402.client import max_amount
from x402.http.clients.requests import wrapRequestsWithPayment
from x402.mechanisms.evm.exact.register import register_exact_evm_client
from x402.mechanisms.evm.signers import EthAccountSigner
from eth_account import Account
import os, requests

account = Account.from_key(os.environ["WALLET_PRIVATE_KEY"])
_client = x402ClientSync()
register_exact_evm_client(_client, EthAccountSigner(account), policies=[max_amount(10_000)])
session = wrapRequestsWithPayment(requests.Session(), _client)

@tool
def skim_read_url(url: str) -> dict:
    """Fetch any web page and return clean Markdown plus structured metadata.

    Strips ads, navigation, scripts, and trackers. Costs $0.002 in USDC,
    paid automatically over x402. Use this whenever the user asks you to
    read, summarize, quote from, or analyze a URL.

    Args:
        url: Absolute https URL of the page to read.
    """
    r = session.post(
        "https://skim402.com/api/v1/read",
        json={"url": url},
        timeout=30,
    )
    r.raise_for_status()
    return r.json()

# pip install openai-agents
# The Skim MCP server (npm: skim-mcp) exposes a read_url tool,
# with x402 payment handled inside the server.
import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStdio

async def main():
    async with MCPServerStdio(
        params={
            "command": "npx",
            "args": ["-y", "skim-mcp"],
            "env": {"SKIM_WALLET_PRIVATE_KEY": "0x..."},
        },
    ) as skim:
        agent = Agent(
            name="Researcher",
            instructions="Use the Skim tools to read web pages.",
            mcp_servers=[skim],
        )
        result = await Runner.run(
            agent, "Summarize https://example.com/article"
        )
        print(result.final_output)

asyncio.run(main())

# 1. First call — server replies 402 with x402 payment instructions
curl -i -X POST https://skim402.com/api/v1/read \
  -H "Content-Type: application/json" \
  -d '{"url":"https://example.com/article"}'

# 2. Sign the x402 challenge with your wallet, then retry with X-PAYMENT:
curl -X POST https://skim402.com/api/v1/read \
  -H "Content-Type: application/json" \
  -H "X-PAYMENT: <base64-payment-payload>" \
  -d '{"url":"https://example.com/article"}'

{
  "url": "https://example.com/article",
  "finalUrl": "https://example.com/article",
  "mode": "basic",
  "markdown": "# Article Title\n\nClean readable content...",
  "text": "Article Title\n\nClean readable content...",
  "metadata": {
    "title": "Article Title",
    "byline": "Jane Doe",
    "siteName": "Example",
    "publishedAt": "2026-01-15T10:00:00Z",
    "excerpt": "First paragraph or summary...",
    "lang": "en",
    "length": 4823
  },
  "structured": null,
  "fetchedAt": "2026-05-17T08:00:00Z"
}

{
  "type": "function",
  "function": {
    "name": "skim_extract_url",
    "description": "Fetch a URL and return typed JSON matching the provided JSON Schema. Skim cleans the page, then constrains an LLM to output values found on the page — never invented from training data. Use this when you need structured data from a web page (a company profile, an article's metadata, a product listing) instead of free-form markdown. Costs $0.015 in USDC, paid automatically over x402.",
    "parameters": {
      "type": "object",
      "properties": {
        "url":    { "type": "string", "description": "Absolute https URL to extract from." },
        "schema": { "type": "object", "description": "JSON Schema describing the desired output shape. Must have type: 'object' at the top level. Use 'description' on each property to hint the model." },
        "instructions": { "type": "string", "description": "Optional natural-language hint to bias extraction (the schema is the primary contract)." }
      },
      "required": ["url", "schema"],
      "additionalProperties": false
    }
  }
}