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This guide walks you through creating an MCP server, writing a tool, testing it in the dashboard, and connecting it to an AI client.

Prerequisites

  • An MCPCore account — sign up free, no credit card required
  • That’s it. No local installs needed.

Step 1 — Create a server

1

Open the dashboard

Go to app.mcpcore.io and navigate to My Servers.
My Servers list page
2

Click New Server

Click the New Server button in the top-right corner.Fill in:
  • Name — a short, descriptive name (e.g. github-tools)
  • Description — optional, but helpful for teams
  • Security mode — start with Public for now; you can change it later
Create server form
3

Save

Click Create server. You’ll be taken to the server detail page, where you can see the endpoint URL and start adding tools.

Step 2 — Write a tool

1

Scroll down to Tools

On the server detail page, scroll down to the Tools section and click Create New Tool.
2

Name your tool

Give your tool a name. Tool names become part of the MCP schema the AI sees — use lowercase snake_case (e.g. fetch_repo_stats).
3

Add a parameter

Click Add parameter and add:
  • Name: repo
  • Type: string
  • Description: GitHub repository in owner/repo format
  • Required: yes
4

Write the code

Paste the following into the code editor:
const res = await sdk.http({
  method: "GET",
  url: `https://api.github.com/repos/${params.repo}`,
});

const data = JSON.parse(res.body());

return {
  stars:    data.stargazers_count,
  forks:    data.forks_count,
  language: data.language,
  topics:   data.topics,
};
Tool code editor
5

Save the tool

Click Save. The tool is now part of your server.

Step 3 — Test it

1

Open the Run panel

With the tool selected, click the Run tab (or the play button in the editor toolbar).
2

Enter a parameter value

In the repo field, enter a real repository name — e.g. anthropics/anthropic-sdk-python.
3

Click Run

Click Run tool. The response panel shows the JSON output within a second or two.
Run panel showing tool output

Step 4 — Connect to an AI client

Copy the Endpoint URL from the server detail page and add it to your AI client:

What’s next?