๐งฉ FastMCP Prompts Example
A small, focused tutorial showing how to build MCP prompts with FastMCP โ reusable, parameterized message templates that any MCP client (Claude Desktop, IDEs, custom agents) can discover and render.
๐ Perfect as a first step into the Model Context Protocol before diving into tools and resources.
๐ 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.
โจ 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 โ 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.
๐ 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:

๐ Test with the MCP Inspector
The fastest way to explore the prompts is the MCP Inspector โ 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 โ Launch the Inspector:
uv run fastmcp dev inspector main.py
You'll see output like this, and your browser opens automatically:
๐ MCP Inspector is up and running at:
http://localhost:6274/?MCP_PROXY_AUTH_TOKEN=<session-token>
โ๏ธ Proxy server listening on localhost:6277
If the browser doesn't open, copy the full URL (including the token) from the terminal.
Step 2 โ Connect to the server. The connection form is pre-filled (transport STDIO, command fastmcp run main.py). Just click Connect โ the indicator turns green when the handshake succeeds.
Step 3 โ 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 โ 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 โ See the interesting cases:
- On
summarize_prompt, notice thelengthandtonefields only accept theLiteralvalues from the type hints โ that's the argument schema in action. - On
code_review_prompt, paste any snippet ascodeand notice the result is three messages (userโassistantโuser), not one โ a pre-seeded conversation.
When you're done, stop the Inspector with Ctrl+C in the terminal.
๐ฅ๏ธ 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.
๐ก No API key needed. Claude Desktop uses your Claude account, and this MCP server only serves prompt templates โ 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.
๐๏ธ Project structure
.
โโโ main.py # The MCP server โ 3 prompt patterns, fully commented
โโโ assets/ # Screenshots used in this README
โโโ pyproject.toml # Project metadata & dependencies
โโโ uv.lock # Locked dependency versions
โโโ README.md
๐ Learn more
- FastMCP documentation โ the framework used here
- FastMCP: Prompts guide โ deep dive on the prompt API
- Model Context Protocol โ the open protocol specification
- MCP: Prompts concept โ how clients consume prompts
๐ ๏ธ Tech stack
| Technology | Role |
|---|---|
| Python 3.12+ | Language |
| FastMCP 3.x | MCP server framework |
| uv | Dependency & environment management |
๐ License
This project is licensed under the MIT License โ see the LICENSE file for details.
Made with โค๏ธ for the MCP community. Follow @mcoding_off for more tutorials.