Agent Skill to Python Mcp Server Generator
Agent Skill to Python Mcp Server Generator is a verified SKILL blueprint on Promptally in Fullstack & Backend Engineering optimized for leading AI models. Use this skill when the user wants to create a new Model Context Protocol (MCP) server in Python. Also use it to expose Python functions, an API, or a database to AI clients as MCP tools. The skill makes a uv project with the MCP Python SDK v2 (MCPServer), typed tools, in-memory tests, and client configuration. Do not use it for an MCP client or for a server in another language. Available to explore, customize with pre-filled variables, and copy with zero authentication required.
Technical Specifications
| Specification | Value |
|---|---|
| Artifact type | SKILL (Fullstack & Backend Engineering) |
| Compatible engines | Universal / Model Agnostic |
| Input variables | None (pre-filled) |
| Approximate tokens | 1,728 |
| Source file | SKILL.md |
| Access tier | Free public (MIT) |
Pre-Filled Template
---
name: python-mcp-server-generator
description: 'Use this skill when the user wants to create a new Model Context Protocol (MCP) server in Python. Also use it to expose Python functions, an API, or a database to AI clients as MCP tools. The skill makes a uv project with the MCP Python SDK v2 (MCPServer), typed tools, in-memory tests, and client configuration. Do not use it for an MCP client or for a server in another language.'
compatibility: 'Requires uv, Python 3.10 or later, and network access to install packages. The MCP Inspector also requires Node.js.'
---
# Python MCP Server Generator
Create a Model Context Protocol (MCP) server in Python with the official [MCP Python SDK](https://github.com/modelcontextprotocol/python-sdk) v2. SDK v2 supports the MCP specification revision [2026-07-28](https://modelcontextprotocol.io/specification/2026-07-28). The same server also serves clients that use earlier revisions.
## Workflow
Copy this checklist and track your progress:
- [ ] Step 1: Create the project.
- [ ] Step 2: Write the server.
- [ ] Step 3: Write the tests.
- [ ] Step 4: Run the tests until they pass.
- [ ] Step 5: Configure the client.
### Step 1: Create the project
Run these commands:
```bash
uv init --app --no-package project-name
cd project-name
uv add "mcp[cli]>=2,<3"
uv add --dev pytest
```
Then delete `main.py`. The server goes in `server.py`.
- Without `--no-package`, uv makes a `src/` package layout, and the tests cannot import `server.py`.
- `uv init` makes the `.gitignore` file. Do not write a different one.
### Step 2: Write the server
Start from this template:
```python
from mcp.server import MCPServer
from mcp.server.mcpserver.exceptions import ToolError
mcp = MCPServer("Demo", version="0.1.0")
@mcp.tool()
def divide(a: float, b: float) -> float:
"""Divide a by b."""
if b == 0:
raise ToolError("b must not be zero.")
return a / b
if __name__ == "__main__":
mcp.run() # stdio is the default transport
```
Then change the template for the request of the user:
1. Replace `divide` with the tools that the user needs.
2. Give each tool full type hints and a docstring. The SDK makes the input schema from the type hints. The docstring becomes the tool description.
3. Return a Pydantic model or a `TypedDict` when the client needs machine-readable data. The SDK makes the output schema from the return type.
4. Use `async def` for I/O. The SDK runs a sync tool on a worker thread.
5. Mark a read-only tool with `@mcp.tool(annotations=ToolAnnotations(read_only_hint=True))` (from `mcp.types`). Use `destructive_hint=True` for a destructive tool.
6. Add resources (`@mcp.resource("users://{user_id}")`) and prompts (`@mcp.prompt()`) only when the user asks for them.
Use stdio by default. Read [references/streamable-http.md](references/streamable-http.md) only when the user asks for a remote server or an HTTP server.
### Step 3: Write the tests
Put `test_server.py` next to `server.py`. Write a test for each tool and for each `ToolError`:
```python
import pytest
from mcp import Client
from server import mcp
@pytest.mark.anyio
async def test_divide():
async with Client(mcp) as client:
result = await client.call_tool("divide", {"a": 6, "b": 3})
assert result.structured_content == {"result": 2.0}
@pytest.mark.anyio
async def test_divide_by_zero():
async with Client(mcp) as client:
result = await client.call_tool("divide", {"a": 1, "b": 0})
assert result.is_error
assert "must not be zero" in result.content[0].text
```
- The in-memory `Client` needs no subprocess and no port. It connects with the 2026-07-28 revision.
- The `mcp` package installs `anyio`, which supplies the `anyio` marker. Do not add `pytest-asyncio`.
### Step 4: Run the tests until they pass
1. Run `uv run pytest`.
2. If a test fails, read the error. Fix the server or the test.
3. Run `uv run pytest` again.
4. Continue only when all tests pass.
### Step 5: Configure the client
For VS Code, write `.vscode/mcp.json`:
```json
{
"servers": {
"demo": {
"type": "stdio",
"command": "uv",
"args": ["--directory", "/absolute/path/to/project", "run", "server.py"]
}
}
}
```
For Claude Desktop, run `uv run mcp install server.py`.
Tell the user these commands:
- `uv run server.py` starts the stdio server. The server waits for a host on stdin and prints nothing.
- `uv run mcp dev server.py` opens the MCP Inspector. The Inspector needs Node.js.
## Gotchas
SDK v2 and the 2026-07-28 revision changed many SDK v1 patterns. Do not copy SDK v1 examples.
- SDK v2 removed `FastMCP` and `mcp.server.fastmcp`. Import the server class with `from mcp.server import MCPServer`.
- Import `Context`, `Image`, `Audio`, `Resolve`, `Elicit`, `ElicitationResult`, `AcceptedElicitation`, `Message`, `UserMessage`, and `AssistantMessage` from `mcp.server.mcpserver`.
- Give the server name as the first `MCPServer` argument. Give all other constructor arguments as keyword arguments. Their positional order changed in SDK v2.
- Set `version`. If you do not set it, the server reports an empty version.
- Give the transport options (`transport`, `host`, `port`, `json_response`, `stateless_http`, `transport_security`) to `run()`, not to `MCPServer(...)`.
- The SDK v2 types use snake_case fields, for example `read_only_hint`, `structured_content`, and `is_error`.
- Raise `ToolError` for an error that the model must read. For other exceptions, the model gets only a generic error message.
- Do not raise `MCPError` for a tool failure. The client gets a protocol error, not a tool result with `is_error`. Many hosts do not show this error to the model.
- In a stdio server, stdout is the protocol channel. Do not call `print()`. Log to stderr with the `logging` module.
- Do not use `ctx.elicit()`. It fails on a 2026-07-28 connection. For user input during a tool call, annotate a parameter with `Resolve(fn)`. Return `Elicit(message, Model)` from `fn`.
- Send list change notifications with `await ctx.notify_tools_changed()`. A 2026-07-28 connection drops `ctx.session.send_tool_list_changed()`.
- For stdio and HTTP, the lifespan runs one time, when the server starts. Each in-memory `Client(mcp)` in a test runs the lifespan again. Read its object with `ctx.request_context.lifespan_context`.
- The 2026-07-28 revision deprecates these features ([SEP-2577](https://github.com/modelcontextprotocol/modelcontextprotocol/pull/2577)). Do not add them to a new server:
- **Sampling** (`ctx.session.create_message()`): Call the LLM provider API directly.
- **Protocol logging** (`ctx.log()`, `ctx.info()`, and similar methods): Use the standard `logging` module.
- **Roots** (`ctx.session.list_roots()`): Get paths from tool parameters, resource URIs, or the server configuration.
- The 2026-07-28 revision has no SSE transport. Use Streamable HTTP.
How to use this skill
- Review the pre-filled example and source files above.
- Copy the template or download
SKILL.md, then use it in your model, IDE, or workflow tool. - Compare your result with the sample output when one is provided.
Frequently Asked Questions
How do I use Agent Skill to Python Mcp Server Generator?
Open the skill on Promptally, review the pre-filled example, then copy the template or download SKILL.md and paste it into your model, IDE or workflow tool. Agent Skill to Python Mcp Server Generator is a static blueprint with no dynamic variables. Copy it and use it as-is.
Is Agent Skill to Python Mcp Server Generator free?
Yes. Agent Skill to Python Mcp Server Generator is free to view, copy and download on Promptally without creating an account. It is published under the MIT license.
What variables does Agent Skill to Python Mcp Server Generator need?
Agent Skill to Python Mcp Server Generator is a static blueprint with no dynamic variables. Copy it and use it as-is.