while comprehensive coverage gives agents flexibility to compose operations. Performance varies by client—some clients benefit from code execution that combines basic tools

Mar 20, 2026

Coding & Debugging

PromptBeginner5 minmarkdown

Agents benefit from concise tool descriptions and the ability to filter/paginate results. Design tools that return focused

relevant data. Some clients support code execution which can help agents filter and process data efficiently.

Mar 20, 2026

Coding & Debugging

PromptBeginner5 minmarkdown

description: Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services

whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

Mar 20, 2026

Coding & Debugging

PromptBeginner5 minmarkdown

Add your new code as a separate file (e.g.

gokhan_architect.py)?

Mar 20, 2026

Coding & Debugging

PromptBeginner5 minmarkdown

python

Would you like me to:

Mar 20, 2026

Coding & Debugging

PromptBeginner5 minmarkdown

Act as a Master Prompt Architect & Context Engineer. You are the world's most advanced AI request architect. Your mission is to convert raw user intentions into high-performance

error-free

Mar 20, 2026

Find agent skills by outcome

* This server provides tools to interact with Example API

const truncatedData = data.slice(0

- Return complete

const data = await apiRequest(params.limit

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

- The `register*` methods provide better type safety

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

2. **Load each task instruction** and in parallel using the MCP server and tools

Remember to parallelize solving tasks to avoid running out of context

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

After understanding the API and tools

- Store API keys in environment variables

- **Return pagination metadata**: Include `has_more`

- **Python**: `{service}_mcp` (e.g.

Prioritize comprehensive API coverage. List endpoints to implement

- [🐍 Python Guide](./reference/python_mcp_server.md) - Module organization

- **Language**: TypeScript (high-quality SDK support and good compatibility in many execution environments e.g. MCPB. Plus AI models are good at generating TypeScript code

Review the service's API documentation to identify key endpoints

Balance comprehensive API endpoint coverage with specialized workflow tools. Workflow tools can be more convenient for specific tasks

Agents benefit from concise tool descriptions and the ability to filter/paginate results. Design tools that return focused

description: Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services

Add your new code as a separate file (e.g.

python

Act as a Master Prompt Architect & Context Engineer. You are the world's most advanced AI request architect. Your mission is to convert raw user intentions into high-performance

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

2. Load each task instruction and in parallel using the MCP server and tools

- Return pagination metadata: Include `has_more`

- Python: `{service}_mcp` (e.g.

- Language: TypeScript (high-quality SDK support and good compatibility in many execution environments e.g. MCPB. Plus AI models are good at generating TypeScript code