From agentic-bundle-aas-agent-mcp-builder
Builds MCP servers and tools from scratch covering the full lifecycle: specification, implementation, testing, deployment, and registry publishing. Supports TypeScript and Python.
How this skill is triggered — by the user, by Claude, or both
Slash command
/agentic-bundle-aas-agent-mcp-builder:mcp-tool-developerThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Expert at building Model Context Protocol (MCP) servers that give AI agents new capabilities. Covers the full MCP development lifecycle: specification, implementation, testing, deployment, and registry publishing. Supports both TypeScript and Python with production-ready patterns.
Expert at building Model Context Protocol (MCP) servers that give AI agents new capabilities. Covers the full MCP development lifecycle: specification, implementation, testing, deployment, and registry publishing. Supports both TypeScript and Python with production-ready patterns.
This skill understands MCP specification primitives (tools, resources, prompts, sampling), transport options (stdio, SSE, Streamable HTTP), and the tool design patterns that make MCP servers reliable and composable.
Identify what capabilities the server should expose:
Choose the transport:
Define input/output schemas before writing implementation:
{
name: "tool_name",
description: "What this tool does (visible to the LLM)",
inputSchema: {
type: "object",
properties: { ... },
required: [ ... ]
}
}
Create the server with proper error handling, validation, and logging. Use the official MCP SDK for TypeScript (@modelcontextprotocol/sdk) or Python (mcp).
Test with the MCP Inspector, validate tool schemas, handle edge cases, then deploy locally or remotely.
import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
import { z } from "zod";
const server = new McpServer({ name: "my-tools", version: "1.0.0" });
server.tool("greet", "Greet someone by name",
{ name: z.string().describe("Person's name") },
async ({ name }) => ({ content: [{ type: "text", text: `Hello, ${name}!` }] })
);
const transport = new StdioServerTransport();
await server.connect(transport);
Wrap an external API as an MCP tool with auth, rate limiting, and error handling:
Problem: LLM calls tools with wrong parameters Solution: Improve tool descriptions and add examples in the description field. The LLM reads descriptions to decide how to call tools.
Problem: Tool times out on large inputs Solution: Add input size validation and pagination. Stream large responses instead of buffering.
api-integration-architect - For API design patterns used in MCP toolssecurity-audit-code-reviewer - For reviewing MCP server code securitynpx claudepluginhub sickn33/agentic-awesome-skills --plugin agentic-bundle-aas-agent-mcp-builder94plugins reuse this skill
First indexed Jun 3, 2026
Showing the 6 earliest of 94 plugins
Builds MCP servers and tools from scratch covering the full lifecycle: specification, implementation, testing, deployment, and registry publishing. Supports TypeScript and Python.
Builds MCP servers in Python (FastMCP) or Node/TypeScript (MCP SDK) to expose third-party APIs as LLM tools. Handles scaffolding, adding tools, evaluations, and tool interface design.
Guides creating high-quality MCP servers with agent-centric design, tool implementation (Python FastMCP or Node/TypeScript SDK), and error handling. Use when building MCP servers for external API integration.