MCP Hero

Ready-to-use MCP ServersFREE

When Agents Struggle, MCP Solves It — Counting, Dates, Units, and More. Experiment freely. Deploy reliably. We host for you.

https://mcp.hebo.ai/aikit/

Discover available toolkits

Counting
How many r’s are there in “Strawberry”?
Date TimeComing Soon
Convert dates and times into specific time zones
What do you need?
Request new toolkits
Use our pre-hosted tools with any LLM & AI SDK

Get started in 60 seconds

import { createMCPClient } from '@ai-sdk/mcp';

const mcpClient = await createMCPClient({
  transport: {
    type: 'http',
    url: 'https://mcp.hebo.ai/aikit/',
  },
}); 

const { count_letters } = await mcpClient.tools();

const result = await streamText({
  model: "openai/gpt-oss-20b",
  tools: { count_letters },
  prompt: "How many r's in Strawberry?",
  onFinish: async () => {
    await mcpClient.close();
  },
});

Why we are building mcp.hebo.ai

We were experimenting with agents and needed something quick to test whether MCP actually works —not only in theory, but end-to-end, against a real server. Most MCP servers we found lived on GitHub, which was great for learning, but meant self-hosting, wiring, and maintenance just to run an experiment.

At the same time, we kept discovering the same truth: there’s a whole class of things agents are not good at. Counting, validation, precise lookups, deterministic logic—these aren’t model problems, they need tools.

The official MCP SDK didn’t make this easier. While it has plenty of examples, they’re very low-level and often overly complicated, making it hard to see how everything fits together in a real system.

At the end of the day, tools are just simple functions with a human readable description of their functionality, which agents can use to decide when to call them. And MCP is just a way to access them remotely.

So mcp.hebo.ai became our shortcut: a live MCP server, real tools, and a place to prove MCP works by actually using it. What started as a test harness stuck around, because once the tools exist, you don’t want to rebuild them every time.

We’ll keep adding tools over time, focusing on the kinds of capabilities agents consistently struggle with. Join us on our journey via X (@heboai) or reach out to us on Discord.

Hebo MCP exists so experimenting with MCP doesn’t start with infrastructure—and agents don’t have to pretend they can do everything.