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A production-grade Model Context Protocol (MCP) server that exposes internal employee directory and project management systems to AI models.

Обзор

A production-grade Model Context Protocol (MCP) server that exposes internal employee directory and project management systems to AI models. This MCP server standardizes how AI assistants access your internal data. Instead of building custom integrations for each AI model, you define your data once, and any MCP-compatible client—Claude, ChatGPT, or your custom app—can use it without modification. - – Find team members by name, email, role, or department - – Query active, completed, and on-hold projects - – Identify who's working on what projects - – Explore departments and team hierarchies - – Role-based data filtering per user - – Complete audit trail of all data access - – Health checks, error handling, Docker-ready - Node.js 22+ - npm or yarn - PostgreSQL (for production use; can be mocked in dev) The server will start on http://localhost:3100/mcp by default.

README

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Internal Data MCP Server

A production-grade Model Context Protocol (MCP) server that exposes internal employee directory and project management systems to AI models.

Overview

This MCP server standardizes how AI assistants access your internal data. Instead of building custom integrations for each AI model, you define your data once, and any MCP-compatible client—Claude, ChatGPT, or your custom app—can use it without modification.

Key Capabilities

  • Employee Directory Search – Find team members by name, email, role, or department
  • Project Management – Query active, completed, and on-hold projects
  • Team Composition – Identify who’s working on what projects
  • Organization Structure – Explore departments and team hierarchies
  • Secure Access Control – Role-based data filtering per user
  • Audit Logging – Complete audit trail of all data access
  • Production Ready – Health checks, error handling, Docker-ready

Architecture

┌─────────────────┐
│   AI Models     │
│  (Claude, etc)  │
└────────┬────────┘
         │
    HTTP/stdio
         │
┌────────▼──────────────────────┐
│    MCP Server (Node.js)        │
│  - Tools (Data Operations)     │
│  - Resources (Context Data)    │
│  - Authentication/Audit        │
└────────┬──────────────────────┘
         │
    ┌────┴──────┬──────────┐
    │            │          │
┌───▼──┐    ┌────▼───┐  ┌──▼────┐
│ DB   │    │ APIs   │  │ Docs   │
└──────┘    └────────┘  └────────┘

Quick Start

Prerequisites

  • Node.js 22+
  • npm or yarn
  • PostgreSQL (for production use; can be mocked in dev)

Installation

# Clone or download the repository
cd internal-data-mcp

# Install dependencies
npm install

# Build TypeScript
npm run build

Development

# Run the HTTP server (dev mode)
npm run dev

# Run with stdio transport (for Claude Desktop)
npm run stdio

# Type check
npm run type-check

The server will start on http://localhost:3100/mcp by default.

Production

# Build for production
npm run build

# Start the server
npm start

# Or use Docker
docker build -t internal-data-mcp .
docker run -p 3100:3100 -e INTERNAL_DB_URL="postgres://..." internal-data-mcp

Configuration

Environment Variables

# Database connection string
INTERNAL_DB_URL=postgres://user:password@localhost/internal_data

# Server port (default: 3100)
PORT=3100

# Node environment
NODE_ENV=production

Database Schema

The server expects the following PostgreSQL tables:

-- Employees table
CREATE TABLE employees (
  id UUID PRIMARY KEY,
  name TEXT NOT NULL,
  email TEXT UNIQUE NOT NULL,
  department TEXT NOT NULL,
  role TEXT NOT NULL,
  manager_id UUID,
  start_date DATE NOT NULL
);

-- Projects table
CREATE TABLE projects (
  id UUID PRIMARY KEY,
  name TEXT NOT NULL,
  status VARCHAR(20) NOT NULL CHECK (status IN ('active', 'completed', 'on_hold')),
  lead_id UUID NOT NULL REFERENCES employees(id),
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Установка

docker run -p 3100:3100 -e INTERNAL_DB_URL="postgres://..." internal-data-mcp
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Конфигурация

{ "mcpServers": { "internal-data": { "command": "node", "args": ["path/to/internal-data-mcp/dist/index.js"], "env": { "INTERNAL_DB_URL": "postgres://...", "PORT": "3100" } } } }