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

Coding & Debugging

PromptBeginner5 minmarkdown

Master Prompt Architect & Context Engineer

---

Mar 20, 2026

Find agent skills by outcome

description: `Search for users in the Example system by name

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

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

<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

- Example: if finding a paper name

- Questions must be designed so there is a single

- Email address

- 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

- **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

Master Prompt Architect & Context Engineer

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

- 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