Claude MCP Enterprise Assistant

The Model Context Protocol (MCP) represents a standardized approach to connecting AI assistants with external tools and data sources. Claude’s native MCP support makes it ideal for enterprise deployments requiring secure, auditable tool use.

MCP Architecture

┌─────────────────────────────────────────────────────┐
│                  Claude Agent                        │
│         (Claude 3.5 Sonnet + MCP Client)            │
├─────────────────────────────────────────────────────┤
│                MCP Protocol Layer                    │
│    ┌──────────────────────────────────────────┐     │
│    │          Tool Discovery & Invocation      │     │
│    │          Resource Access & Updates        │     │
│    │          Prompt Templates                 │     │
│    └──────────────────────────────────────────┘     │
├─────────────────────────────────────────────────────┤
│              MCP Server Ecosystem                    │
│  ┌─────────┐ ┌─────────┐ ┌─────────┐ ┌─────────┐   │
│  │ GitHub  │ │  Slack  │ │ G-Drive │ │Postgres │   │
│  │  MCP    │ │   MCP   │ │   MCP   │ │   MCP   │   │
│  └─────────┘ └─────────┘ └─────────┘ └─────────┘   │
│  ┌─────────┐ ┌─────────┐ ┌─────────┐ ┌─────────┐   │
│  │ Custom  │ │   RAG   │ │ Linear  │ │ Notion  │   │
│  │  API    │ │ Server  │ │   MCP   │ │   MCP   │   │
│  └─────────┘ └─────────┘ └─────────┘ └─────────┘   │
├─────────────────────────────────────────────────────┤
│              External Services                       │
│      (GitHub, Slack, Databases, APIs, etc.)         │
└─────────────────────────────────────────────────────┘

Why MCP?

Feature	Benefit
Standardized Protocol	Tools work across different AI assistants
Security Model	Built-in authentication and authorization
Resource Abstraction	Access files, databases, APIs uniformly
Composability	Mix and match servers for your use case

Example: Custom RAG Server

import { Server } from "@modelcontextprotocol/sdk/server";

const server = new Server({
  name: "rag-server",
  version: "1.0.0"
});

server.setRequestHandler("tools/call", async (request) => {
  if (request.params.name === "search_docs") {
    const query = request.params.arguments.query;
    const results = await vectorSearch(query);
    return { content: [{ type: "text", text: JSON.stringify(results) }] };
  }
});

When to Use This Stack

• Enterprise deployments requiring standard tool interfaces
• Teams wanting to build reusable tool infrastructure
• Projects needing fine-grained security and audit controls
• Organizations betting on MCP as an industry standard