FastMCP Prompts Example

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Python FastMCP MCP uv

A small, focused tutorial showing how to build MCP prompts with FastMCP — reusable, parameterized message templates that any MCP client (Claude Desktop, IDEs, custom agents) can discover and render.

📚 Perfect as a first step into the Model Context Protocol before diving into tools and resources.

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📖 What are MCP prompts?

While MCP tools let a model do things and resources let it read things, prompts are user-controlled templates: the client lists them, fills in their arguments, and injects the rendered messages into the conversation. Think of them as slash commands for LLMs.

✨ What this example covers

main.py demonstrates the three patterns you'll use most, from simplest to most powerful:

#	Prompt	Pattern	Concept demonstrated
1	research_prompt	Return a plain str	Simplest form — auto-wrapped in a single user message
2	summarize_prompt	Optional + constrained args	Literal types & defaults become a client-visible argument schema
3	code_review_prompt	Return list[Message]	Seed a full multi-turn conversation (user + assistant messages)

Along the way you'll also see: naming, descriptions, tags, and server instructions.

🚀 Quickstart

Prerequisites: Python 3.12+ and uv.

# 1. Clone and enter the project
git clone https://github.com/mohamedelamraoui1/fastMCP-2-0-example.git
cd fastMCP-2-0-example

# 2. Install dependencies
uv sync

# 3. Run the server (stdio transport)
uv run main.py

If everything is set up correctly, you'll see the FastMCP banner and the server waiting for a client on stdio:

🔍 Test with the MCP Inspector

The fastest way to explore the prompts is the MCP Inspector — a web UI for poking at any MCP server. It requires Node.js (the Inspector is an npm package that FastMCP launches for you).

Step 1 — Launch the Inspector:

uv run fastmcp dev inspector main.py

You'll see output like this, and your browser opens automatically:

🚀 MCP Inspector is up and running at:
   http://localhost:6274/?MCP_PROXY_AUTH_TOKEN=<session-token>
⚙️ Proxy server listening on localhost:6277

If the browser doesn't open, copy the full URL (including the token) from the terminal.

Step 2 — Connect to the server. The connection form is pre-filled (transport STDIO, command fastmcp run main.py). Just click Connect — the indicator turns green when the handshake succeeds.

Step 3 — List the prompts. Open the Prompts tab and click List Prompts. You should see all three: research_prompt, summarize_prompt, and code_review_prompt, each with its description.

Step 4 — Render a prompt. Click a prompt, fill in its arguments in the form (e.g. topic = "quantum computing" for research_prompt), and click Get Prompt. The right panel shows the exact messages the server returns.

Step 5 — See the interesting cases:

• On summarize_prompt, notice the length and tone fields only accept the Literal values from the type hints — that's the argument schema in action.
• On code_review_prompt, paste any snippet as code and notice the result is three messages (user → assistant → user), not one — a pre-seeded conversation.

When you're done, stop the Inspector with Ctrl+C in the terminal.

🖥️ Use it from Claude Desktop

Add the server to your Claude Desktop config (claude_desktop_config.json):

{
  "mcpServers": {
    "prompt-examples": {
      "command": "uv",
      "args": ["run", "--directory", "C:/absolute/path/to/fastMCP-2-0-example", "main.py"]
    }
  }
}

Restart Claude Desktop, then look for the prompts in the + (attachments) menu.

💡 No API key needed. Claude Desktop uses your Claude account, and this MCP server only serves prompt templates — it never calls an LLM itself. You'd only need an Anthropic API key if you wrote your own client that sends the rendered prompts to the API.

🗂️ Project structure

.
├── main.py          # The MCP server — 3 prompt patterns, fully commented
├── assets/          # Screenshots used in this README
├── pyproject.toml   # Project metadata & dependencies
├── uv.lock          # Locked dependency versions
└── README.md

📚 Learn more

• FastMCP documentation — the framework used here
• FastMCP: Prompts guide — deep dive on the prompt API
• Model Context Protocol — the open protocol specification
• MCP: Prompts concept — how clients consume prompts

🛠️ Tech stack

Technology	Role
Python 3.12+	Language
FastMCP 3.x	MCP server framework
uv	Dependency & environment management

📄 License

This project is licensed under the MIT License — see the LICENSE file for details.

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Made with ❤️ for the MCP community. Follow @mcoding_off for more tutorials.