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

Mar 21, 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 21, 2026

Coding & Debugging

PromptBeginner5 minmarkdown

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

gokhan_architect.py)?

Mar 21, 2026

Coding & Debugging

PromptBeginner5 minmarkdown

python

Would you like me to:

Mar 21, 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 21, 2026

Find agent skills by outcome

This tool searches across all user profiles in the Example platform

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

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

- The `register*` methods provide better type safety

Remember to parallelize solving tasks to avoid running out of context

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

<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

- Questions must be designed so there is a single

- Store API keys in environment variables

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

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

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

- **MCP Protocol**: Start with sitemap at `https://modelcontextprotocol.io/sitemap.xml`

Prioritize comprehensive API coverage. List endpoints to implement

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

Review the service's API documentation to identify key endpoints

- **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

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

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

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`

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

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

- MCP Protocol: Start with sitemap at `https://modelcontextprotocol.io/sitemap.xml`

- 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