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Quick Start

This guide will help you get started with the QPanda3 Runtime MCP Server quickly.

New to quantum computing or MCP? Check out our comprehensive Getting Started Guide for a complete beginner's walkthrough with detailed explanations.

One-Click Setup

The fastest way to get started is using the setup scripts. See Configuration for the full CLI reference.

# Linux / macOS — minimal (non-interactive)
./scripts/setup_configure.sh

# Windows PowerShell — minimal (non-interactive)
.\scripts\setup_configure.ps1

For a fully automated setup with your API key and MCP client configured in one command:

# Linux / macOS — one-line full setup
./scripts/setup_configure.sh --api-key YOUR_KEY --mcp claude-desktop
# Windows PowerShell — one-line full setup
.\scripts\setup_configure.ps1 -ApiKey "YOUR_KEY" -McpClient claude-desktop

To be guided through each step interactively:

# Linux / macOS
./scripts/setup_configure.sh --interactive
# Windows PowerShell
.\scripts\setup_configure.ps1 -Interactive

Prerequisites

Requirement Description
Python 3.10+ Python interpreter (up to 3.13)
Origin Quantum Account API key
MCP-compatible AI Assistant Claude Desktop, Cline, or similar

Basic Usage

1. Set Up Credentials

Copy the example file and edit it:

cp .env.example .env
# Then edit .env with your API key

Or use environment variables:

export QPANDA3_API_KEY="your_api_key_here"

2. Run the Server

python -m qpanda3_runtime_mcp_server

Common Tasks

Setting Up Your Account

The first step is to configure your Origin Quantum account:

# Using the MCP tool
await setup_origin_quantum_account_tool(
    api_key="your_api_key"
)

Listing Available Devices

To see what quantum devices are available:

devices = await list_qpu_devices_tool()
for device in devices["devices"]:
    print(f"Device: {device['name']} (ID: {device['id']})")
    print(f"  Qubits: {device['num_qubits']}")
    print(f"  Operational: {device['operational']}")

Running a Quantum Circuit

Here's how to run a Bell state circuit:

# Define the circuit in OriginIR format
circuit = """QINIT 2
CREG 2
H q[0]
CNOT q[0],q[1]
MEASURE q[0],c[0]
MEASURE q[1],c[1]"""

# Submit the sampling task
result = await sample_tool(
    circuit=circuit,
    device_id="20",
    shots=1000
)

task_id = result["task_id"]
print(f"Task submitted: {task_id}")

# Check task status
status = await get_task_status_tool(task_id)
print(f"Status: {status['task_status']}")

# Get results when done
if status["task_status"] == "DONE":
    results = await get_task_results_tool(task_id)
    print(f"Results: {results['results']}")

Running Expectation Estimation

To estimate the expectation value of an observable:

# Define circuit (without measurements)
circuit = """QINIT 2
CREG 2
H q[0]
CNOT q[0],q[1]"""

# Define observable
observable = {"Z0 Z1": 1.0}

# Submit estimation task
result = await estimate_tool(
    circuit=circuit,
    observable=observable,
    device_id="20"
)

task_id = result["task_id"]

Using with AI Assistants

Cline Configuration

Add the following to your Cline MCP settings:

{
  "mcpServers": {
    "qpanda3-runtime": {
      "command": "/path/to/qpanda3-runtime-mcp-server/.venv/bin/python",
      "args": ["-m", "qpanda3_runtime_mcp_server"],
      "cwd": "/path/to/qpanda3-runtime-mcp-server",
      "env": {
        "QPANDA3_API_KEY": "your_api_key"
      },
      "disabled": false
    }
  }
}

Example Prompts

Once connected, you can ask your AI assistant:

  • "List all available QPU devices"
  • "Get properties of device ID 20"
  • "Run a Bell state circuit on device 20 with 1000 shots"
  • "Check the status of my task"
  • "Show me an example quantum circuit"

Available Circuit Resources

The server provides pre-built quantum circuits:

Resource URI Description
circuits://bell-state Bell state (2-qubit entanglement)
circuits://ghz-state GHZ state (3-qubit entanglement)
circuits://random Quantum random number generator
circuits://superposition Single qubit superposition

Next Steps