Turn any URL into agent-callable MCP tools.

// wmcp.sh is a real MCP server — add it to Claude Code / Cursor / Codex / VS Code.
{
  "mcpServers": {
    "wmcp": {
      "type": "http",
      "url": "https://wmcp.sh/mcp/u/<base64url-of-your-url>"
    }
  }
}
// One site → /mcp/u/<b64url>   ·   compose many → /mcp/url?url=a&url=b
// tools/list is free; live tools/call uses your Bearer key.

curl 'https://wmcp.sh/api/v1/tools?url=https://www.allbirds.com/products/mens-wool-runners'

// Plain fetch — works everywhere.
const r = await fetch(
  `https://wmcp.sh/api/v1/tools?url=${encodeURIComponent(url)}`,
  { headers: { authorization: `Bearer ${API_KEY}` } }
);
const { tools } = await r.json();

// Pass wmcp tools straight into Anthropic SDK.
const tools = (await fetch(`https://wmcp.sh/api/v1/tools?url=${url}`).then(r => r.json())).tools;
const msg = await anthropic.messages.create({
  model: "claude-opus-4-8",
  tools: tools.map(t => ({
    name: t.name,
    description: t.description,
    input_schema: t.inputSchema || { type: "object" }
  })),
  messages: [{ role: "user", content: "Add the size 10 to my cart." }]
});

# LangChain — wrap each wmcp tool as a StructuredTool.
from langchain.tools import StructuredTool
import requests

data = requests.get(f"https://wmcp.sh/api/v1/tools?url={url}").json()
tools = [
  StructuredTool.from_function(
    func=lambda args, t=t: call_wmcp(t["name"], args, url),
    name=t["name"],
    description=t["description"],
  )
  for t in data["tools"]
]

// OpenAI function-calling format.
const { tools } = await (await fetch(`https://wmcp.sh/api/v1/tools?url=${url}`)).json();
const completion = await openai.chat.completions.create({
  model: "gpt-4o",
  tools: tools.map(t => ({
    type: "function",
    function: {
      name: t.name,
      description: t.description,
      parameters: t.inputSchema || { type: "object", properties: {} }
    }
  })),
  messages: [{ role: "user", content: "Find the cheapest variant." }]
});