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TonyQ-AI
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mcp-builder

Design, implement, and test Model Context Protocol servers with TypeScript or Python.

9|Updated Jul 3, 2026
Search Tags:#api#integration#backend#tooling#mcp#model context protocol
One-click install
npx skills add https://github.com/TonyQ-AI/agents-workflow --skill mcp-builder-tonyq-ai
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: mcp-builder
Source: https://github.com/TonyQ-AI/agents-workflow/tree/main/skills/mcp-builder
Command: npx skills add https://github.com/TonyQ-AI/agents-workflow --skill mcp-builder-tonyq-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires @modelcontextprotocol/sdk, zod, pydantic, mcp.

What problem does it solve?

This skill addresses the complexity of designing, implementing, and testing Model Context Protocol (MCP) servers, ensuring that AI assistants can reliably connect to and interact with external tools, resources, and prompts.

Core Features & Use Cases

  • Standardized Architecture: Provides a clear project structure for both TypeScript and Python-based MCP servers.
  • Robust Tool Design: Offers best practices for tool naming, parameter validation using Zod/Pydantic, and effective error handling.
  • Testing & Debugging: Includes strategies for unit/integration testing and using the MCP Inspector for interactive validation.
  • Use Case: A developer needs to build a custom MCP server to allow an AI to query a private SQL database; this skill provides the exact patterns for secure tool definition, input validation, and resource management.

Quick Start

Use the mcp-builder skill to generate a project structure and implementation guide for a new TypeScript-based MCP server.

Frequently Asked Questions about mcp-builder

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build a production-grade Model Context Protocol server?▼

To build a Model Context Protocol server, you need a standardized project structure for TypeScript or Python, robust tool design with Zod or Pydantic for parameter validation, and secure error handling for standardized protocol communication.

How do I validate input parameters when defining custom MCP tools?▼

You validate custom MCP tool parameters using Zod for TypeScript servers or Pydantic for Python servers, ensuring robust input validation and secure error handling before the AI assistant interacts with the external tool.

Can I use both Python and TypeScript to create MCP servers?▼

Yes, you can create MCP servers using either TypeScript or Python, applying standardized architecture patterns and best practices for tool naming, resource management, and prompt definitions across both language implementations.

What is the best way to test and debug an MCP server integration?▼

The best way to test an MCP server integration involves executing unit and integration testing strategies alongside using the MCP Inspector for interactive validation of tool connectivity and external resource management.

How do I allow an AI assistant to query a private SQL database via MCP?▼

To allow an AI to query a private SQL database via MCP, you define secure custom tools and resources on your MCP server, applying strict input validation and error handling patterns to manage the external database connectivity.

What are the limitations when deploying MCP servers for external tool integration?▼

Limitations when deploying MCP servers involve ensuring robust input validation and secure error handling are strictly maintained, as standardized protocol communication requires careful management of custom tool and resource definitions to prevent integration failures.

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