---

title: QuantumArchitect MCP emoji: ⚛️ colorFrom: indigo colorTo: purple sdk: gradio sdk_version: 6.0.1 app_file: app.py pinned: false license: mit short_description: Quantum Circuit Architect & MCP Server for AI Agents tags:

• building-mcp-track-enterprise
• building-mcp-track-consumer
• building-mcp-track-creative
• Google-Gemini-API

---

VIDEO: https://youtu.be/E1Ailx1X1YE SOCIAL: https://www.linkedin.com/posts/nicolas-larenas_quantumarchitect-mcp-a-hugging-face-space-activity-7401024993893044225-RF-R?utm_source=share&utm_medium=member_desktop&rcm=ACoAADmu0wIBjvA0DVdHvqncNUVTEW72gbiGUps

QuantumArchitect-MCP 🔬⚛️

A Python-based MCP (Model Context Protocol) Server for Quantum Circuit creation, validation, and evaluation. This serves as a "Quantum Logic Engine" that AI Agents can call upon to validate, score, and execute quantum logic.

🚀 Features

• Circuit Creation: Generate Bell States, GHZ States, QFT, Grover's Algorithm, and VQE Ansatz circuits
• Circuit Validation: Syntax checking, connectivity validation for real hardware, unitarity verification
• Circuit Evaluation: Statevector simulation, noise estimation, resource estimation
• Circuit Scoring: Complexity metrics, expressibility scores, hardware fitness evaluation
• MCP Endpoints: Full MCP protocol support for AI Agent integration
• Hardware Profiles: Support for IBM, Rigetti, and other quantum hardware topologies

📦 Installation

For Hugging Face Spaces

This project is designed to run directly on Hugging Face Spaces. Simply clone and deploy!

Local Installation

pip install -r requirements.txt
python app.py

🚀 Quick Start

1. Start the Application

python app.py

The app will start at http://127.0.0.1:7861

2. Build Your First Circuit

1. Open the web interface in your browser
2. Go to the "Circuit Builder" tab
3. Click the "H" button to add a Hadamard gate
4. Click "Simulate" to see the results
5. View the Bloch sphere visualization of the qubit state

3. Try a Bell State

1. Go to the "Templates" tab
2. Select "Bell State" from the dropdown
3. Click "Load Template"
4. Click "Simulate" to see entangled output (50/50 probabilities)

4. Validate a Circuit

1. Go to the "Validate" tab
2. Paste or enter QASM code
3. Select target hardware (e.g., "ibm_eagle")
4. Click "Validate" to check syntax, connectivity, and unitarity

🔧 Project Structure

QuantumArchitect-MCP/
├── app.py                          # Main entry point (Gradio + MCP)
├── requirements.txt                # Dependencies
├── pyproject.toml                  # Project configuration
├── src/
│   ├── mcp_server/                 # MCP Protocol handling
│   │   ├── server.py               # MCP capabilities definition
│   │   ├── schemas.py              # JSON schemas for I/O
│   │   └── context_provider.py     # Resource providers
│   ├── core/                       # Quantum engine core
│   │   ├── circuit_parser.py       # QASM/circuit parsing
│   │   ├── dag_representation.py   # Internal DAG model
│   │   └── exceptions.py           # Custom exceptions
│   ├── plugins/                    # Modular components
│   │   ├── creation/               # Circuit generation
│   │   ├── validation/             # Circuit validation
│   │   ├── evaluation/             # Circuit evaluation
│   │   └── scoring/                # Circuit scoring
│   └── data/                       # Knowledge base
│       ├── hardware_profiles/      # Hardware topology configs
│       └── reference_circuits/     # Standard algorithm references
└── tests/                          # Test suite

🎯 MCP Endpoints

Creation Tools

• create_bell_state: Generate a 2-qubit Bell state circuit
• create_ghz_state: Generate an N-qubit GHZ state
• create_qft: Generate Quantum Fourier Transform circuit
• create_grover: Generate Grover's search algorithm
• create_vqe_ansatz: Generate VQE variational ansatz

Validation Tools

• validate_syntax: Check circuit syntax validity
• validate_connectivity: Verify hardware topology compatibility
• validate_unitarity: Check if circuit is properly unitary

Evaluation Tools

• simulate_statevector: Get ideal simulation results
• estimate_noise: Estimate circuit noise accumulation
• estimate_resources: Calculate required shots and resources

Scoring Tools

• score_complexity: Get circuit depth, gate count, width
• score_expressibility: Evaluate VQC expressibility (QML)
• score_hardware_fitness: Rate circuit for specific hardware

🖥️ Usage

Web Interface

Access the Gradio UI at the deployed URL or http://localhost:7860 for local runs.

MCP Integration

Connect your AI Agent to the MCP endpoints:

# Example: Claude Desktop configuration
{
    "mcpServers": {
        "quantum-architect": {
            "url": "https://your-space.hf.space/mcp"
        }
    }
}

📚 Learning Path Integration

This tool follows the "Zero to Hero" quantum computing curriculum:

1. Level 0 (Beginner): Use creation templates (Bell, GHZ states)
2. Level 1 (Practitioner): Validate circuits against real hardware
3. Level 2 (Advanced): Evaluate noise and optimize for NISQ devices
4. Level 3 (PhD/Hero): Score expressibility and develop new algorithms

🤖 AI Agent Integration

Available MCP Tools

Tool	Description	Parameters
mcp_create_circuit	Create from template	template_name, num_qubits, parameters_json
mcp_parse_qasm	Parse OpenQASM code	qasm_code, qasm_version
mcp_build_circuit	Build custom circuit	num_qubits, gates_json, measurements_json
mcp_validate_circuit	Validate circuit	qasm_code, hardware_target, check_connectivity, check_unitary
mcp_check_hardware	Check hardware compatibility	qasm_code, hardware_name
mcp_simulate	Simulate circuit	qasm_code, shots, include_statevector, noise_model
mcp_get_statevector	Get ideal statevector	qasm_code
mcp_estimate_fidelity	Estimate hardware fidelity	qasm_code, hardware_name
mcp_score_circuit	Score circuit	qasm_code, hardware_name
mcp_compare_circuits	Compare multiple circuits	circuits_json, hardware_name
mcp_get_gate_info	Gate documentation	gate_name
mcp_get_algorithm_info	Algorithm explanation	algorithm_name
mcp_list_hardware	List hardware profiles	-
mcp_list_templates	List circuit templates	-
mcp_get_learning_path	Get learning resources	level

Supported Hardware Profiles

• IBM Eagle (127 qubits, heavy-hex topology)
• Rigetti Aspen (80 qubits, octagonal topology)
• IonQ Aria (25 qubits, all-to-all connectivity)

Circuit Templates

• bell_state - Maximally entangled 2-qubit state
• ghz_state - N-qubit GHZ entangled state
• w_state - N-qubit W state
• superposition - Uniform superposition
• qft - Quantum Fourier Transform
• grover - Grover's search algorithm
• vqe - VQE variational ansatz
• qaoa - QAOA optimization circuit

🧪 Running Tests

pytest tests/ -v

📄 License

MIT License - See LICENSE file for details.

🙏 Acknowledgments

Built with:

• Gradio - UI and MCP integration
• Qiskit - Quantum computing framework
• Pydantic - Data validation