Which integrations are available for this server?

Supports integration with Codeium AI coding assistant through MCP configuration, allowing quantum computing operations within the Codeium development environment. Hosts the project repository and documentation on GitHub, with GitHub Actions workflows for automated testing and deployment of the MCP server. Utilizes GitHub Actions for continuous integration and deployment workflows, automating testing and documentation building for the MCP server. Provides direct integration with Origin Quantum computing services through QPanda3 Runtime, enabling AI assistants to access quantum processing units, execute circuits, and manage quantum computing tasks. References Qiskit MCP Server as a related implementation, providing similar quantum computing integration patterns for IBM quantum services through the Model Context Protocol.

How do I use QPanda3 Runtime MCP Server?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@QPanda3 Runtime MCP Server sample a 3-qubit quantum circuit on the most available QPU device" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

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QPanda3 Runtime MCP Server

by OriginQ

Overview Schema Related Servers Score Discussions

Python

Remote

QPanda3 Runtime MCP Server

Python 3.10+ FastMCP License Documentation

A Model Context Protocol (MCP) server that enables AI assistants to interact with Origin Quantum computing services through QPanda3 Runtime.

Features

Account Management: Configure and manage Origin Quantum cloud account authentication
Device Management: List and query available QPU devices
Quantum Computing Tasks: Execute sampling and estimation tasks
Batch Operations: Run multiple circuits efficiently
Multi-Objective Decisions: CircuitObservableBinding for complex optimization
Task Management: Query task status, retrieve results, cancel tasks
Example Circuits: Provides common quantum circuit example resources

Documentation

Document	Description
English Docs	English documentation site
中文文档	Chinese documentation site
Getting Started	Complete beginner's guide - START HERE
Installation Guide	Detailed installation instructions
Quick Start	Fast setup for experienced users
Configuration	Environment and client configuration
User Guide	Detailed feature documentation
API Reference	Auto-generated API documentation

Installation

One-Click Setup (Recommended)

The project provides setup scripts that automate the entire process:

Linux / macOS:

git clone https://github.com/OriginQ/qpanda3-runtime-mcp-server.git
cd qpanda3-runtime-mcp-server
chmod +x scripts/setup_configure.sh
./scripts/setup_configure.sh

Windows (PowerShell):

git clone https://github.com/OriginQ/qpanda3-runtime-mcp-server.git
cd qpanda3-runtime-mcp-server
.\scripts\setup_configure.ps1

The script handles everything: dependency setup, API key configuration, and MCP client setup.

See Installation Guide for manual install options.

Quick Start

# 1. Configure your API key
cp .env.example .env
# Edit .env and set QPANDA3_API_KEY=your_api_key_here

# 2. Run the server
.venv/bin/python -m qpanda3_runtime_mcp_server       # Linux/macOS
# .venv\Scripts\python.exe -m qpanda3_runtime_mcp_server  # Windows

See Configuration for MCP client setup and advanced options.

MCP Tools

Account Management

Tool	Description
`setup_origin_quantum_account_tool`	Configure Origin Quantum cloud account authentication
`list_saved_accounts_tool`	List saved account information (session-based)
`active_account_info_tool`	Get currently active account information

Device Management

Tool	Description
`list_qpu_devices_tool`	List all available QPU (Quantum Processing Unit) devices
`get_qpu_properties_tool`	Get detailed properties of a specific QPU device

Quantum Computing Tasks

Tool	Description
`sample_tool`	Execute quantum circuit sampling task on a QPU device
`estimate_tool`	Execute expectation estimation task for a quantum circuit
`batch_sample_tool`	Batch execute multiple quantum circuit sampling tasks
`batch_estimate_tool`	Batch execute estimation tasks for multiple circuits with one observable

Multi-Objective Decision (CircuitObservableBinding)

Tool	Description
`create_circuit_observable_binding_tool`	Create a binding for multiple circuits and observables
`add_product_rule_tool`	Add Cartesian product combination rule (all combinations)
`add_zip_rule_tool`	Add one-to-one combination rule (paired combinations)
`estimate_with_binding_tool`	Execute estimation using the created binding
`list_bindings_tool`	List all stored CircuitObservableBinding objects
`delete_binding_tool`	Delete a stored CircuitObservableBinding object

Task Management

Tool	Description
`get_task_status_tool`	Get the execution status of a task (`PENDING`/`RUNNING`/`DONE`/`FAILED`/`CANCELLED`)
`get_task_results_tool`	Get the computation results of a completed task
`cancel_task_tool`	Cancel a running or pending task
`list_my_tasks_tool`	List user's recent quantum computing tasks

MCP Resources

Resource URI	Description
`qpanda://status`	Service status
`circuits://bell-state`	Bell state circuit example
`circuits://ghz-state`	GHZ state circuit example
`circuits://random`	Random number generator circuit
`circuits://superposition`	Superposition circuit example

Example Usage

Configure Account

# Auto-configure via environment variables
# Or call explicitly
await setup_origin_quantum_account_tool(
    api_key="your_api_key"
)

List Devices

devices = await list_qpu_devices_tool()
print(f"Available devices: {devices['total_devices']}")

Execute Sampling Task

# Bell state circuit
circuit = """QINIT 2
CREG 2
H q[0]
CNOT q[0],q[1]
MEASURE q[0],c[0]
MEASURE q[1],c[1]"""

result = await sample_tool(
    circuit=circuit,
    device_id="20",
    shots=1000
)
task_id = result["task_id"]

# Check status and get results
status = await get_task_status_tool(task_id)
if status["task_status"] == "DONE":
    results = await get_task_results_tool(task_id)
    print(f"Measurement results: {results['results']}")

Configure in AI Coding Platforms

Auto-configure: Use ./scripts/setup_configure.sh --mcp claude-desktop (or --mcp cline, --mcp cursor, etc.)

All clients use the same config format (replace /path/to/... with your actual path):

{
  "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_here" }
    }
  }
}

Client	Config File Location
Claude Code	`~/.claude.json`
Claude Desktop	macOS: `~/Library/Application Support/Claude/claude_desktop_config.json`
Cline	`~/.vscode-server/data/User/globalStorage/saoudrizwan.cline/settings/cline_mcp_settings.json`
Cursor	`.cursor/mcp.json` (project root)
Windsurf	`~/.codeium/windsurf/mcp_config.json`

For more clients (Trae etc.), see Configuration Guide.

Development

Install Development Dependencies

uv sync --extra dev --extra test

Run Tests

uv run pytest

Code Linting

uv run ruff check .
uv run mypy src/

Build Documentation

# Install documentation dependencies
uv sync --extra docs

# Build documentation (English + Chinese)
./scripts/build-docs.sh

# Local preview with live reload (language switching supported)
mkdocs serve

Project Structure

qpanda3-runtime-mcp-server/
├── src/
│   └── qpanda3_runtime_mcp_server/
│       ├── __init__.py          # Package entry point
│       ├── server.py            # MCP server definition
│       ├── runtime.py           # QPanda3 Runtime core logic
│       └── utils.py             # Utility functions
├── scripts/
│   ├── setup_configure.sh       # One-click setup (Linux/macOS)
│   ├── setup_configure.ps1      # One-click setup (Windows PowerShell)
│   ├── setup_configure.bat      # One-click setup (Windows CMD)
│   ├── build-docs.sh            # Build all documentation
│   └── serve-docs.sh            # Serve docs with live reload
├── tests/
│   ├── __init__.py
│   ├── conftest.py              # pytest configuration
│   ├── test_server.py           # Server tests
│   └── test_runtime.py          # Runtime tests
├── docs/
│   ├── *.md                     # English documentation (default)
│   └── cn/                      # Chinese documentation
├── mkdocs.yml                   # MkDocs configuration (i18n)
├── .github/
│   └── workflows/               # GitHub Actions workflows
├── pyproject.toml               # Project configuration
├── README.md                    # Project documentation
├── LICENSE                      # Apache 2.0 License
├── .env.example                 # Environment variable example
└── .gitignore                   # Git ignore file

Notes

Default Server: The server connects to https://qpanda3-runtime.qpanda.cn by default. Set QPANDA3_SERVER_URL to override.
Channel: The server uses the qcloud channel by default
Async Support: All tool functions are async functions
Error Handling: All functions return dictionaries containing a status field
Type Hints: Python type hints are used for better code readability

License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

Contributing

See Contributing Guide for details.

Changelog

See Changelog for version history.

Install Server

security – no known vulnerabilities

license - permissive license

quality - A tier

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QPanda3 Runtime MCP Server

Features

Documentation

Installation

One-Click Setup (Recommended)

Quick Start

MCP Tools

Account Management

Device Management

Quantum Computing Tasks

Multi-Objective Decision (CircuitObservableBinding)

Task Management

MCP Resources

Example Usage

Configure Account

List Devices

Execute Sampling Task

Configure in AI Coding Platforms

Development

Install Development Dependencies

Run Tests

Code Linting

Build Documentation

Project Structure

Notes

License

Related Links

Contributing

Changelog

Resources

Looking for Admin?

Tools

Latest Blog Posts

MCP directory API