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AdithyanandanArun

HandoffOS

README.md
# HandoffOS

> **Enterprise Workflow Intelligence through MCP**
>
> **Rules detect. AI explains. MCP acts.**

![MCP](https://img.shields.io/badge/Model%20Context%20Protocol-MCP-blue)
![NitroStack](https://img.shields.io/badge/Built%20with-NitroStack-0A66FF)
![TypeScript](https://img.shields.io/badge/TypeScript-5.x-3178C6)
![License](https://img.shields.io/badge/License-MIT-green)

---

## Overview

Large enterprises don't lose productivity because employees cannot communicate—they lose productivity because work gets **stuck during handoffs between teams**.

Manager approval may be complete, but HR assumes IT has already created a laptop request. Identity provisioning cannot begin until the laptop is allocated, VPN access depends on identity, and onboarding stalls because no system understands the complete workflow.

**HandoffOS** solves this problem by reconstructing enterprise events into a **live workflow state**, detecting bottlenecks using deterministic business rules, explaining them with AI-backed natural language, and exposing workflow capabilities through the **Model Context Protocol (MCP)**.

Rather than acting as another enterprise chatbot, HandoffOS functions as a **Workflow Intelligence Engine** that any MCP-compatible AI client can use.

---

# Problem Statement

Modern enterprises operate using multiple disconnected systems such as:

- HR Platforms
- Ticketing Systems
- Email
- Calendar
- Documentation
- Task Boards

Each platform understands only a small portion of an organization's workflow.

This creates problems such as:

- Unknown workflow bottlenecks
- Missed SLAs
- Poor ownership visibility
- Delayed onboarding
- Manual follow-ups
- Lack of operational transparency

Organizations know **tasks**.

They rarely know the **state of the workflow**.

---

# Solution

HandoffOS continuously transforms enterprise events into a single workflow graph.

Instead of showing independent tasks, it understands:

- Workflow Dependencies
- Ownership
- Critical Paths
- Workflow Health
- Business Rules

The system identifies the root blocker, explains why it exists using evidence, predicts downstream impact, and recommends or executes the next approved action.

---

# Key Features

### Live Workflow State

Visualizes the current workflow and immediately highlights blocked stages.

---

### Deterministic Rules Engine

Business logic detects:

- Missing Dependencies
- Missing Owners
- SLA Violations
- Critical Path Blocks
- Missing Documentation

Rules determine facts.

AI never invents them.

---

### Evidence-Based Explanations

Every blocker includes supporting evidence such as:

- Completed approvals
- Missing tasks
- Dependency chains
- Rule violations

This eliminates hallucinations and increases trust.

---

### Workflow Health Score

Calculates workflow health based on measurable factors including:

- Blocked Nodes
- SLA Violations
- Critical Path Risk
- Downstream Impact

The score is explainable and reproducible.

---

### Workflow Simulation

"What happens if this blocker is resolved?"

The workflow is recalculated instantly, showing:

- Updated Health
- New Critical Path
- Estimated Completion Time

---

### Execute Approved Actions

Supports controlled workflow execution such as:

- Creating Tasks
- Assigning Owners
- Scheduling Activities
- Updating Workflow State
- Writing Audit Logs

---

### MCP Native

HandoffOS exposes its capabilities using the **Model Context Protocol**.

Any compatible client—including NitroStudio, Claude Desktop, and future MCP-enabled assistants—can access the same workflow intelligence through a standard interface.

---

# Architecture

```
Enterprise Events
        │
        ▼
 Event Store
        │
        ▼
Workflow State Builder
        │
        ▼
Deterministic Rules Engine
        │
        ▼
Evidence Generation
        │
        ▼
MCP Server
 ├── Resources
 ├── Tools
 └── Prompts
        │
        ▼
NitroStudio • Claude • Cursor • MCP Clients
```

---

# Demonstration Workflow

Our prototype demonstrates **Employee Onboarding**.

```
Manager Approval
        │
        ▼
HR Verification
        │
        ▼
Laptop Allocation
        │
        ▼
Identity Access
        │
        ▼
VPN Setup
        │
        ▼
Developer Access
        │
        ▼
Orientation
```

If **Laptop Allocation** is delayed,

every downstream activity becomes blocked.

HandoffOS detects the root cause immediately.

---

# MCP Resources

```
workflow://onboard-priya/state

workflow://onboard-priya/events

workflow://onboard-priya/findings

workflow://onboard-priya/audit-log

workflow://rules
```

---

# MCP Tools

- detect_blockers
- simulate_resolution
- execute_action
- ingest_event
- plan_next_actions

---

# MCP Prompts

- explain_blocker
- manager_summary

---

# Technology Stack

- TypeScript
- Node.js
- NitroStack
- Model Context Protocol (MCP)

---

# Installation

```bash
git clone https://github.com/AdithyanandanArun/HandOffOS.git

cd HandOffOS

npm install
```

Run the server:

```bash
npm run start
```

---

# Connect Using an MCP Client

Configure your MCP client:

```json
{
  "mcpServers": {
    "handoffos": {
      "url": "YOUR_SERVER_URL"
    }
  }
}
```

Supported clients include:

- NitroStudio
- Claude Desktop
- Cursor
- Other MCP-compatible clients

---

# Potential Applications

Although demonstrated using employee onboarding, HandoffOS can support:

- Procurement
- Vendor Onboarding
- Customer Support
- Leave Approval
- Incident Response
- Manufacturing Workflows
- IT Service Management

Only the workflow template changes.

The engine remains the same.

---

# Why HandoffOS?

Most AI systems answer questions.

HandoffOS improves workflows.

```
Question
     │
     ▼
Evidence
     │
     ▼
Rules
     │
     ▼
AI Explanation
     │
     ▼
Simulation
     │
     ▼
Approved Action
     │
     ▼
Updated Workflow
```

The result is a transparent, explainable, and actionable workflow intelligence platform.

---

# Team

Developed during the **Agentic AI Hackathon 2026**

---

# License

MIT License

---

> **HandoffOS makes invisible enterprise handoffs visible, explainable, and actionable.**

TDQS

B3.2/5.0

Scored across 13 tools

Disambiguation3/5

Most tools are distinct, but what_if_multi and simulate_resolution both simulate without changing live workflow state, differing mainly in scope (multi-node vs. single resolution), which could confuse an agent. Other tools are clearly separated by action and resource.

Naming Consistency4/5

The naming convention is overwhelmingly verb_noun (ingest_event, detect_blockers, execute_action), but 'what_if_multi' breaks the pattern by not starting with a verb. No camelCase or mixed conventions exist, so the inconsistency is minor.

Tool Count5/5

Thirteen tools is well within the optimal 3-15 range and each tool addresses a distinct aspect of workflow management, from simulation and execution to audit and comparison, so the count feels appropriately scoped.

Completeness3/5

The set covers core workflow operations like simulation, execution, rollback, prediction, and audit, but lacks an explicit approval tool even though plan_next_actions references approvals. Additionally, workflow retrieval is only implicit through compare_workflows, leaving a moderate gap in the lifecycle.

Maintenance

ActivityInactive
ResponsivenessNo issues