MCP Server Say Hello

The Mcp Server Say Hello Py is a lightweight, MCP‑compliant service that delivers personalized greeting messages to AI assistants and their users. It solves the common need for a simple, standardized “hello” endpoint that can be invoked by any MCP‑enabled client—whether that’s a chat assistant, an integration bot, or a custom workflow tool. By providing a single, well‑defined tool () that accepts a username and returns a friendly greeting, developers can quickly demonstrate or test MCP tooling without the overhead of building custom logic.

At its core, the server implements a single REST endpoint () that conforms to MCP v1.2 specifications. When a client sends a JSON payload containing the user’s name, the server responds with a plain‑text greeting wrapped in a standard MCP response structure. This strict adherence to the protocol guarantees that any AI assistant built on MCP will understand and correctly display the greeting, eliminating ambiguity around message formats or error handling. The service’s simplicity also makes it an ideal educational example for new developers learning how to expose tools via MCP.

Key features include:

• Personalized greetings: The tool accepts a parameter and returns “Hello {username}!” in the response text, allowing assistants to personalize interactions with minimal effort.
• Protocol compliance: All request and response schemas follow MCP v1.2, ensuring interoperability across different client implementations.
• Multi‑environment support: The server can be launched with , Docker, or a standard Python installation (), making it adaptable to CI/CD pipelines, local development, and production deployments.
• Explicit tool registration: The README provides a clear registration schema that can be copied into VS Code, Claude Desktop, or Trae CN Desktop configurations, streamlining the integration process.

Typical use cases for this MCP server include:

• Demo and onboarding: Showcasing how an AI assistant can call external tools without writing custom code.
• Testing MCP clients: Providing a predictable, well‑documented endpoint for unit tests or integration checks.
• Personalization hooks: Adding a quick, human‑friendly greeting step in larger conversational flows or workflow automations.

By integrating this server into an AI assistant’s tool registry, developers gain a reliable, protocol‑aligned way to inject dynamic content into conversations. Its straightforward design and clear configuration examples make it a valuable starting point for building more complex MCP services, while also serving as a reference implementation that highlights best practices in tool definition and deployment.