From REST to MCP: Converting Your Regular API Endpoint into an MCP Server Endpoint

In today’s evolving backend architectures—especially with the rise of AI agents and composable applications—traditional REST APIs are giving way to more modular, context-aware systems.

One promising approach is MCP (Module Context Protocol), which allows agents or services to interact using structured context modules instead of rigid endpoints.

Here is a simple walk through how to convert a regular REST API into an MCP-compliant server endpoint, so it can participate in a larger network of intelligent modules.

What Is MCP?

Module Context Protocol (MCP) is an open protocol designed for modular, agent-based systems. Instead of relying solely on routes and parameters like traditional APIs, MCP uses contextual inputs and modular outputs to enable flexible, declarative execution between modules.

It’s particularly useful in AI workflows, no-code platforms, and dynamic app composition.

🎯 Use Case: Basic REST Endpoint Example

Let’s start with a basic REST API endpoint:

GET /weather?city=San+Francisco

This might return:

{ "city": "San Francisco", "temperature": "18°C", "condition": "Sunny" }

Pretty standard. But this API is tied to a URL path, expects a query param, and doesn’t support composability or AI-context.

✅ Goal: Convert it into MCP Format

We want to create a module that adheres to MCP, which accepts structured inputs and returns structured outputs—typically through a POST call.

🧱 Step 1: Define MCP Module Input & Output

Here’s the conceptual shift:

• Input: an object describing what we want, e.g., weather in a city

• Output: a structured response with weather details

Input:

{ "city": "San Francisco" }

Output:

{ "temperature": "18°C", "condition": "Sunny" }

We wrap this in an MCP-compatible schema, often under inputs and outputs:

{ "inputs": { "city": "San Francisco" }, "outputs": { "temperature": "18°C", "condition": "Sunny" } }

🧑‍💻 Step 2: Create MCP Server Handler (Node.js Example)

Let’s say you’re using Express.js. Here’s a simple MCP server handler:

app.post('/mcp/weather', async (req, res) => {
  const { city } = req.body.inputs || {};

  if (!city) {
    return res.status(400).json({
      error: "Missing 'city' in inputs"
    });
  }

  const weatherData = await getWeatherFromDB(city); // Or external API

  res.json({
    outputs: {
      temperature: weatherData.temp,
      condition: weatherData.condition
    }
  });
});

🧪 Step 3: Test MCP Module with Agent or Orchestrator

Once your endpoint is MCP-compliant, it can now be called by any MCP-compatible orchestrator or agent:

{ "module": "weather", "inputs": { "city": "San Francisco" } }

Expected response:

{ "outputs": { "temperature": "18°C", "condition": "Sunny" } }

This opens doors to chaining this with other modules (e.g., travel suggestions based on weather), all declaratively.

🧩 Bonus: Add Metadata

MCP modules often include metadata to help orchestrators:

{ "id": "weather-module", "description": "Returns current weather for a given city", "input_schema": { "city": "string" }, "output_schema": { "temperature": "string", "condition": "string" } }

This can be served at /mcp/weather/meta or embedded in documentation.

🏁 Final Thoughts

Converting your existing REST APIs to MCP server endpoints unlocks a more modular, declarative world where your services can plug into dynamic workflows—especially for AI, no-code, and automation ecosystems.

Start small: wrap your key endpoints in the MCP structure, define clear inputs and outputs, and explore integrating them into an orchestrator. The future is composable—and you’re just one module away.

If you're building MCP-based applications or want help modularizing your backend, feel free to reach out or drop a comment below! 👇