HR-assist MCP server
Enables Claude Desktop to autonomously perform HR operations such as employee onboarding, leave management, meeting scheduling, ticket creation, and email notifications through MCP tool calling.
README
AI-powered HR automation using the Model Context Protocol (MCP) and Claude Desktop.
HR-Assist is an Agentic AI application that enables Claude Desktop to autonomously perform HR operations through MCP tool calling. The system demonstrates multi-step workflow orchestration by automating employee onboarding, leave management, meeting scheduling, ticket creation, and email notifications using natural language commands.
<p align="center">
</p>
🌟 Key Highlights
- 🤖 Agentic AI workflow powered by MCP
- 🛠️ Modular MCP tool ecosystem for Claude Desktop
- 🔄 Multi-step autonomous task orchestration
- 📧 Automated email notifications
- 🎫 IT/Admin ticket automation
- 📅 Meeting scheduling
- 🌴 Leave management
- 🧩 Modular service-oriented architecture
Portfolio Project: This repository was built to demonstrate practical Agentic AI development, MCP server implementation, workflow automation, and tool-calling capabilities for GenAI and AI/ML Engineering roles.
📑 Table of Contents
- System Architecture
- Agent Workflow
- Features
- AI Concepts Demonstrated
- Available MCP Tools
- Tech Stack
- Installation
- Usage
- Future Improvements
- License
🏗️ System Architecture
flowchart LR
U[User] --> C[Claude Desktop]
C --> M[MCP Server]
M --> E[Employee Manager]
M --> L[Leave Manager]
M --> T[Ticket Manager]
M --> ME[Meeting Manager]
M --> EM[Email Service]
E --> D[(In-Memory Data)]
L --> D
T --> D
ME --> D
EM --> SMTP[SMTP Email Server]
Architecture Overview
The project follows a modular service-oriented architecture where Claude Desktop communicates with the MCP server through the Model Context Protocol (MCP). The server exposes multiple HR tools that operate on independent service modules responsible for employee management, leave tracking, meetings, ticketing, and email notifications.
For simplicity and portability, the application uses in-memory data storage seeded with sample employee records at startup. This allows the entire onboarding workflow to be demonstrated without requiring external databases or infrastructure.
🤖 Agent Workflow
The onboarding process is executed as a multi-step AI workflow, where Claude Desktop interprets the user's request, selects the appropriate MCP tools, and coordinates them to complete the entire onboarding process autonomously.
flowchart TD
A[Natural Language Request]
--> B[Claude Desktop]
B --> C[MCP Server]
C --> D{Task Planning}
D --> E[Add Employee]
E --> F[Generate Employee Credentials]
F --> G[Send Welcome Email]
G --> H[Notify Manager]
H --> I[Create IT & Admin Tickets]
I --> J[Schedule Introductory Meeting]
J --> K[Return Final Summary]
Workflow Explanation
Unlike traditional automation scripts that execute predefined functions, the AI agent dynamically determines which MCP tools to invoke based on the user's natural language request.
For a single onboarding request, the agent autonomously:
- Understands the user's intent.
- Plans the sequence of required actions.
- Invokes the appropriate MCP tools.
- Passes relevant context between tool calls.
- Executes the onboarding workflow.
- Returns a consolidated summary after all tasks are completed.
This demonstrates tool calling, workflow orchestration, context propagation, and Agentic AI reasoning using the Model Context Protocol (MCP).
✨ Features
🤖 AI-Powered Employee Onboarding
Automate the complete onboarding process using a single natural language request.
- Add new employees to the HRMS
- Generate employee credentials
- Send personalized welcome emails
- Notify the reporting manager
- Create onboarding tickets (Laptop, ID Card, etc.)
- Schedule introductory meetings
🧑💼 Employee Management
Manage employee information through MCP tools.
- Retrieve employee details
- View employee profiles
- Access manager and contact information
🌴 Leave Management
Simplify leave tracking and requests.
- Check available leave balance
- View leave history
- Apply for leave
📅 Meeting Management
Coordinate employee meetings directly from Claude Desktop.
- Schedule meetings
- View upcoming meetings
- Cancel existing meetings
🎫 Ticket Management
Automate IT and administrative requests.
- Create onboarding tickets
- Track existing tickets
- Update ticket status
📧 Email Automation
Keep employees and managers informed automatically.
- Welcome emails
- Manager notifications
- General email communication
⚡ Natural Language Interface
Interact with the HR system using plain English instead of manually invoking individual tools.
Example:
"Onboard Karan Mehta under Vikram Singh."
"Schedule a meeting for Rahul Sharma."
"How many leaves does Priya Verma have remaining?"
🧠 AI Concepts Demonstrated
This project showcases several core concepts used in modern Generative AI and Agentic AI applications.
| Concept | Implementation |
|---|---|
| Model Context Protocol (MCP) | Exposes HR operations as MCP tools that Claude Desktop can discover and invoke. |
| Agentic AI | Executes complete HR workflows from a single natural language request. |
| Tool Calling | Enables the LLM to invoke structured backend tools instead of generating text alone. |
| Workflow Orchestration | Coordinates multiple dependent tasks such as employee creation, email notifications, ticket generation, and meeting scheduling. |
| Context Propagation | Passes employee information between successive tool calls during workflow execution. |
| Natural Language Interface | Allows users to interact with the HR system using conversational prompts instead of traditional UI forms. |
| Function-Based Tool Design | Each HR operation is exposed as an independent, reusable MCP tool. |
| Service-Oriented Architecture | Business logic is separated into modular services for maintainability and scalability. |
| Prompt-Driven Automation | Complex workflows are initiated through a single user prompt interpreted by Claude Desktop. |
| Email Automation | Integrates automated notifications into the onboarding workflow. |
Why MCP?
Instead of building custom APIs or tightly coupling the AI model with backend services, this project leverages the Model Context Protocol (MCP) to expose HR functionality as standardized tools.
This enables Claude Desktop to:
- Discover available tools automatically
- Invoke tools securely through a standardized interface
- Chain multiple tool calls into autonomous workflows
- Extend the system with new capabilities without modifying the AI client
This design demonstrates how MCP simplifies the development of modular, extensible, and interoperable AI applications.
🛠️ Available MCP Tools
The MCP server exposes a collection of specialized tools that Claude Desktop can invoke to perform HR operations. Each tool is designed to handle a single responsibility, making the system modular, reusable, and easy to extend.
| Category | Tool | Description |
|---|---|---|
| 👤 Employee Management | get_employee_details |
Retrieve an employee's ID, email, manager, and profile information. |
| 👤 Employee Management | add_employee |
Register a new employee in the HRMS. |
| 🌴 Leave Management | get_employee_leaves |
Check an employee's remaining leave balance. |
| 🌴 Leave Management | get_leave_history |
View an employee's historical leave records. |
| 🌴 Leave Management | apply_leaves |
Submit a leave request for specified dates. |
| 📅 Meeting Management | schedule_meeting |
Schedule a meeting between employees. |
| 📅 Meeting Management | cancel_meetings |
Cancel an existing meeting. |
| 📅 Meeting Management | get_meetings |
Retrieve all scheduled meetings for an employee. |
| 🎫 Ticket Management | create_ticket |
Raise IT or administrative requests such as laptops or ID cards. |
| 🎫 Ticket Management | list_ticket |
Retrieve all tickets associated with an employee. |
| 🎫 Ticket Management | update_ticket_status |
Update the status of an existing ticket. |
| 📧 Communication | send_email |
Send automated email notifications. |
Example Tool Chain
A single onboarding request triggers multiple MCP tools behind the scenes.
User Prompt
│
▼
add_employee
│
▼
send_email
│
▼
create_ticket
│
▼
create_ticket
│
▼
schedule_meeting
│
▼
Return Final Summary
This demonstrates how Claude Desktop can orchestrate multiple independent MCP tools to complete a complex HR workflow from a single natural language request.
🛠️ Tech Stack
| Category | Technologies |
|---|---|
| Programming Language | Python 3.11+ |
| AI Framework | Model Context Protocol (MCP) |
| AI Client | Claude Desktop |
| Package Manager | uv |
| Communication | SMTP (Email Notifications) |
| Data Storage | In-Memory Data Structures |
| Configuration | JSON |
| Architecture | Modular Service-Oriented Design |
⚙️ Installation
Prerequisites
Before getting started, ensure you have the following installed:
- Python 3.11+
- uv package manager
- Claude Desktop
- A valid email account with an App Password (required for sending automated emails)
1. Clone the Repository
git clone <repository-url>
cd hr-assist
2. Install Dependencies
Initialize the project:
uv init
Install the required MCP packages:
uv add "mcp[cli]"
3. Configure Claude Desktop
Locate your claude_desktop_config.json file and add the following MCP server configuration:
{
"mcpServers": {
"hr-assist": {
"command": "<YOUR_UV_EXECUTABLE_PATH>",
"args": [
"--directory",
"<YOUR_PROJECT_DIRECTORY_PATH>",
"run",
"server.py"
],
"env": {
"EMAIL": "<YOUR_HOST_EMAIL>",
"EMAIL_PASS": "<YOUR_APP_PASSWORD>"
}
}
}
}
Configuration Variables
| Variable | Description |
|---|---|
<YOUR_UV_EXECUTABLE_PATH> |
Absolute path to the uv executable |
<YOUR_PROJECT_DIRECTORY_PATH> |
Absolute path to this project |
EMAIL |
Email address used to send automated notifications |
EMAIL_PASS |
App Password for your email account (recommended instead of your account password) |
4. Restart Claude Desktop
After saving the configuration:
- Close Claude Desktop.
- Reopen Claude Desktop.
- Verify that the HR-Assist MCP Server appears in the available connectors.
💡 Note: Claude Desktop may continue running in the background even after closing the application. If your MCP server doesn't appear after updating the configuration, open Task Manager, end all Claude processes, and then launch Claude Desktop again. This ensures Claude reloads the updated MCP configuration.
🚀 Usage
Once the MCP server is configured and Claude Desktop is running, you can interact with the HR system using natural language.
Example Prompts
Onboard a New Employee
Add Karan Mehta who will report to Vikram Singh.
Check Leave Balance
How many leaves does Rahul Sharma have remaining?
Apply for Leave
Apply leave for Priya Verma from August 5 to August 7.
Schedule a Meeting
Schedule a one-on-one meeting between Rahul Sharma and Vikram Singh tomorrow at 10 AM.
Create an IT Ticket
Create a laptop replacement ticket for Karan Mehta.
The AI agent automatically selects the appropriate MCP tools and executes the requested workflow without requiring users to manually invoke individual tools.
👨💻 About Me
Hi, I'm Keshav Sharma 👋
I'm an aspiring Generative AI & AI/ML Engineer passionate about building intelligent systems using LLMs, Agentic AI, Model Context Protocol (MCP), Machine Learning, and Deep Learning.
I enjoy transforming AI concepts into practical applications by developing projects focused on workflow automation, intelligent agents, computer vision, and natural language processing.
This repository is part of my portfolio, showcasing my approach to designing modular, production-inspired AI systems that combine software engineering best practices with modern AI technologies.
🔗 Connect With Me
- 💻 GitHub: https://github.com/yash-s27
- 📧 Email: yash27sharma10@gmail.com
If you have feedback, collaboration ideas, or opportunities related to AI/ML or Generative AI, I'd love to connect!
📄 License
This project is licensed under the MIT License. See the LICENSE file for details.
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。