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{

Before finalizing your Python MCP server implementation

ensure:

- [ ] Tools enable complete workflows

not just API endpoint wrappers

Creative

4. Proper Imports: Group imports (standard library

third-party

return await api_call(resource_id

api_key)

- `ctx.log_info(message

data)` / `ctx.log_error()` / `ctx.log_debug()` - Logging

Creative

await ctx.report_progress(0.25

Starting search...)

'''Search for users in the Example system by name

async def _make_api_request(endpoint: str

method: str = GET

query: str = Field(...

description=Search string to match against names/emails

This server provides tools to interact with Example API

including user search

email: str

# Email address (e.g.

- query (str): Search string to match against names/emails (e.g.

john

Search for users in the Example system by name

async def _make_api_request(endpoint: str

method: str = GET

data = await api_request(limit=params.limit

offset=params.offset)

def validate_email(cls

v: str) -> str:

email: str = Field(...

description=User's email address

The official MCP Python SDK provides FastMCP

a high-level framework for building MCP servers. It provides:

This document provides Python-specific best practices and examples for implementing MCP servers using the MCP Python SDK. It covers server setup

tool registration patterns

- [ ] Tools enable complete workflows

not just API endpoint wrappers

* This server provides tools to interact with Example API

including user search

const data = await apiRequest(params.limit

params.offset);

email: string

// Email address