jeremylongshore

COMPLETE Context for Vertex AI: Life Sciences MCP Plugin Generation

Name: COMPLETE Context for Vertex AI: Life Sciences MCP Plugin Generation
Author: jeremylongshore

AI community intermediate

SOURCE https://github.com/jeremylongshore/claude-code-plugins-plus-skills

Description

COMPLETE Context for Vertex AI: Life Sciences MCP Plugin Generation skill

Installation

This entry records only its repository, not the path inside it, so there is no exact command to give. Open the source below and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

Repository README

This is the README for jeremylongshore/claude-code-plugins-plus-skills, shared by 25 entries in this directory. It describes the repository, not this entry specifically.

COMPLETE Context for Vertex AI: Life Sciences MCP Plugin Generation

What You're Building (Technologies Invented AFTER Your Training)

1. Claude Code (Released 2025)

A desktop CLI tool for software development
Users can install "plugins" to extend functionality
Plugins distributed via JSON-based marketplaces

2. Model Context Protocol (MCP) - Announced November 2024

NOT in your training data - this is NEW
Open standard by Anthropic for connecting AI to external tools
Uses JSON-RPC 2.0 over stdin/stdout
Client-server architecture

**MCP Architecture:**

┌──────────────┐
│  Claude Code │ ← MCP Client (the host application)
│  (Desktop)   │
└──────┬───────┘
       │ Communicates via JSON-RPC 2.0 messages
       │ Over standard input/output (stdio)
       ▼
┌──────────────┐
│  MCP Server  │ ← What you're building (TypeScript/Node.js)
│  (This code) │
└──────────────┘
       │
       │ Makes API calls to external services
       ▼
┌──────────────┐
│   PubMed API │
│   10x Cloud  │
│   Synapse    │
└──────────────┘

3. MCP Protocol Details (You Must Know This)

**JSON-RPC 2.0 Message Types:**

// Request (Client → Server)
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "search_pubmed",
    "arguments": { "query": "cancer" }
  }
}

// Response (Server → Client)
{
  "jsonrpc": "2.0",
  "id": 1,
  "result": {
    "content": [{ "type": "text", "text": "Found 1000 articles" }]
  }
}

**Three Core Primitives:**

**Tools** - Functions the server exposes

// List available tools
Request: { "method": "tools/list" }
Response: { "tools": [{ "name": "search_pubmed", "description": "...", "inputSchema": {...} }] }

// Execute a tool
Request: { "method": "tools/call", "params": { "name": "search_pubmed", "arguments": {...} } }
Response: { "content": [...] }

**Resources** - Data the server provides

Request: { "method": "resources/list" }
Response: { "resources": [{ "uri": "pubmed://article/12345", "name": "..." }] }

**Prompts** - Templates for AI interactions

Request: { "method": "prompts/list" }
Response: { "prompts": [{ "name": "research-outline", "description": "..." }] }

4. TypeScript MCP Server Template (EXACT Pattern to Follow)

import { Server } from "@modelcontextprotocol/sdk/server/index.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
import {
  CallToolRequestSchema,
  ListToolsRequestSchema,
} from "@modelcontextprotocol/sdk/types.js";
import { z } from "zod";

class PubMedMCPServer {
  private server: Server;

  constructor() {
    // Initialize MCP server
    this.server = new Server(
      {
        name: "pubmed-research-master",
        version: "1.0.0",
      },
      {
        capabilities: {
          tools: {},  // We provide tools
        },
      }
    );

    this.setupToolHandlers()