@apitier/mcp-server

MCP (Model Context Protocol) server that exposes all APITier utility APIs as tools for AI agents.

Tools Available

Setup

1. Get your API keys

Sign up at apitier.com. Each APITier service has its own subscription and API key. You only need keys for the services you want to use — tools without a configured key are automatically omitted from the MCP tool list.

2. Install

npm install -g @apitier/mcp-server
# or run directly without installing:
npx @apitier/mcp-server

Claude Desktop

Add to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):

{
  "mcpServers": {
    "apitier": {
      "command": "npx",
      "args": ["@apitier/mcp-server"],
      "env": {
        "APITIER_POSTCODE_KEY":     "key-from-postcode-subscription",
        "APITIER_EMAIL_KEY":        "key-from-email-subscription",
        "APITIER_PHONE_KEY":        "key-from-phone-subscription",
        "APITIER_VAT_KEY":          "key-from-vat-subscription",
        "APITIER_BARCODE_KEY":      "key-from-barcode-subscription",
        "APITIER_CONVERT_DATA_KEY": "key-from-data-conversion-subscription"
      }
    }
  }
}

Only set keys for services you have subscribed to. Restart Claude Desktop — you will see only the tools for your active subscriptions.

Cursor / Windsurf / other MCP clients

{
  "mcp": {
    "servers": {
      "apitier": {
        "command": "npx",
        "args": ["@apitier/mcp-server"],
        "env": {
          "APITIER_API_KEY": "your-api-key-here"
        }
      }
    }
  }
}

LangChain (Python)

from mcp import ClientSession, StdioServerParameters
from mcp.client.stdio import stdio_client
from langchain_mcp_adapters.tools import load_mcp_tools
from langgraph.prebuilt import create_react_agent
from langchain_anthropic import ChatAnthropic

async def main():
    server_params = StdioServerParameters(
        command="npx",
        args=["@apitier/mcp-server"],
        env={"APITIER_API_KEY": "your-api-key"},
    )

    async with stdio_client(server_params) as (read, write):
        async with ClientSession(read, write) as session:
            await session.initialize()
            tools = await load_mcp_tools(session)

            model = ChatAnthropic(model="claude-sonnet-4-6")
            agent = create_react_agent(model, tools)

            result = await agent.ainvoke({
                "messages": "Validate this email: test@example.com and look up postcode SW1A 1AA"
            })
            print(result["messages"][-1].content)

Vercel AI SDK (TypeScript)

import { experimental_createMCPClient as createMCPClient } from "ai";
import { Experimental_StdioMCPTransport as StdioMCPTransport } from "ai/mcp-stdio";
import { anthropic } from "@ai-sdk/anthropic";
import { generateText } from "ai";

const mcp = await createMCPClient({
  transport: new StdioMCPTransport({
    command: "npx",
    args: ["@apitier/mcp-server"],
    env: { APITIER_API_KEY: process.env.APITIER_API_KEY! },
  }),
});

const tools = await mcp.tools();

const { text } = await generateText({
  model: anthropic("claude-sonnet-4-6"),
  tools,
  prompt: "Validate the email user@example.com and generate a QR code for https://apitier.com",
});

await mcp.close();

Environment Variables

Development

git clone https://github.com/apitier/apitier-mcp-server.git
cd apitier-mcp-server
npm install
npm run build
APITIER_API_KEY=your-key node dist/index.js

To test with the MCP inspector:

npx @modelcontextprotocol/inspector npx @apitier/mcp-server

Set APITIER_API_KEY in the inspector's environment variables panel.

Example Agent Prompts

Once connected to Claude Desktop, you can say:

• "Validate this list of emails and tell me which ones are invalid: ..."
• "Look up UK postcode EC1A 1BB and fill in the address form"
• "Generate a QR code for our company website with our logo"
• "I have a CSV file — convert it to JSON"
• "Verify this VAT number before I send the invoice: GB123456789"
• "Validate these phone numbers and tell me which country each is from: ..."