mcp-architect

What problem does it solve?

This skill guides teams in implementing the Model Context Protocol to connect LLMs to external data and tools, enabling robust, standardized integration across MCP Servers, Clients, and Tools for AI agents.

Core Features & Use Cases

• Interface Definition: Define Tools (functions) the MCP server will expose, Resources (data) the agent can access, and JSON Schemas for tool arguments.
• SDK Selection & Setup: Use official MCP SDKs (mcp-python-sdk or mcp-typescript-sdk) to scaffold projects and ensure compatibility.
• Server Implementation: Implement input validation with Pydantic (Python) or Zod (TS), handle errors with structured messages, and maintain stateless tools.
• Transport & Deployment: Choose Stdio for local agents or SSE for remote setups, and containerize with Docker for predictable deployments.
• Security & Compliance: Restrict filesystem access, avoid sensitive operations without authorization flows, and document all tools with docstrings.

Quick Start

Use the MCP Architect skill to scaffold an MCP server with a simple tool, define a strict input schema, implement validation, and run the server via Docker for a local Gemini agent.