Find agent skills by outcome

- In your <summary> tags

you must explain:

- [ ] Tools enable complete workflows

not just API endpoint wrappers

Before finalizing your Python MCP server implementation

ensure:

4. Proper Imports: Group imports (standard library

third-party

- `ctx.log_info(message

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

return await api_call(resource_id

api_key)

await ctx.report_progress(0.25

Starting search...)

async def _make_api_request(endpoint: str

method: str = GET

This server provides tools to interact with Example API

including user search

async def _make_api_request(endpoint: str

method: str = GET

data = await api_request(limit=params.limit

offset=params.offset)

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);

This tool searches across all user profiles in the Example platform

supporting partial matches and various search filters. It does NOT create or modify users

│ └── constants.ts # Shared constants (API_URL

CHARACTER_LIMIT

- DO NOT use: Old deprecated APIs such as `server.tool()`

`server.setRequestHandler(ListToolsRequestSchema

<question>Look for pull requests that modified files in the /api directory and were merged between January 1 and January 31

2024. How many different contributors worked on these PRs?</question>

After understanding the API and tools

USE the MCP server tools:

- Questions must be designed so there is a single

clear answer

- Store API keys in environment variables

never in code

3. Be action-oriented: Start with verbs (get

list