Claude Desktop이 Qiskit 및 Qiskit Aer를 사용하여 양자 회로를 생성, 시각화 및 시뮬레이션할 수 있도록 하는 MCP(Model Context Protocol) 서버입니다.
Claude Desktop에 연결하면 다음과 같이 자연스럽게 대화할 수 있습니다:
"벨 상태(Bell state)를 생성하고 1024번의 샷으로 시뮬레이션해 줘"
"GHZ 회로 다이어그램을 보여줘"
"높은 노이즈 환경에서 벨 상태를 실행하고 무엇이 바뀌었는지 설명해 줘"
"이 QASM 문자열로 사용자 지정 회로를 만들어 줘"
Claude가 자동으로 기본 도구를 호출하므로 수동으로 도구를 실행할 필요가 없습니다.
Related MCP server: Qiskit MCP Server
3가지 도구: create_circuit, visualize_circuit, run_simulation
5가지 사전 설정 회로: Bell state, GHZ-3, Superposition, Deutsch-Jozsa, Random-4
사용자 지정 QASM: 유효한 OpenQASM 2.0 문자열 지원
노이즈 모델링: 이상적(Ideal), 낮은 노이즈(p=0.001), 높은 노이즈(p=0.01) (탈분극 오류 사용)
1가지 리소스: resource://noise-presets — 사용 가능한 노이즈 구성 목록
1가지 프롬프트: simulate_walkthrough — 가이드 대화 템플릿
Python 3.13+
Anaconda 또는 기타 Python 환경 관리자
git clone <repo-url>
cd qiskit-sim-mcppip install -e .이 명령은 Python 환경에 mcp[cli], qiskit 및 qiskit-aer를 설치합니다.
python -c "
import asyncio
from quantum_mcp_demo.server import mcp
tools = asyncio.run(mcp.list_tools())
resources = asyncio.run(mcp.list_resources())
prompts = asyncio.run(mcp.list_prompts())
print('Tools:', [t.name for t in tools])
print('Resources:', [r.uri for r in resources])
print('Prompts:', [p.name for p in prompts])
"예상 출력:
Tools: ['create_circuit', 'visualize_circuit', 'run_simulation']
Resources: [AnyUrl('resource://noise-presets')]
Prompts: ['simulate_walkthrough']uv run mcp dev src/quantum_mcp_demo/server.py브라우저에서 http://localhost:6274를 엽니다. Claude Desktop에 연결하기 전에 Tools 탭을 사용하여 각 도구를 수동으로 호출해 보세요.
Claude Desktop 설정 파일을 찾습니다:
OS | 경로 |
macOS |
|
Windows |
|
mcpServers 객체 안에 다음 항목을 추가합니다:
{
"mcpServers": {
"qiskit-sim-mcp": {
"command": "/opt/anaconda3/bin/python",
"args": [
"-m",
"quantum_mcp_demo.server"
]
}
}
}참고:
/opt/anaconda3/bin/python을 실제 Python 경로로 바꾸세요.which python을 실행하여 경로를 찾을 수 있습니다.
Claude Desktop을 완전히 종료(macOS의 경우 Cmd+Q)한 후 다시 엽니다. 새 대화에서 채팅 입력창의 망치 아이콘(🔨)이 보이면 MCP 도구가 로드된 것입니다.
"벨 상태 회로를 만들고, 다이어그램을 보여준 다음, 이상적인 노이즈와 높은 노이즈 환경에서 각각 1024번 시뮬레이션해 줘."
Claude는 다음을 호출합니다:
create_circuit(preset="bell") → circuit_id 획득
visualize_circuit(circuit_id=...) → H + CNOT 게이트 다이어그램 표시
run_simulation(circuit_id=..., shots=1024, noise_preset="ideal") → ~50% |00⟩, ~50% |11⟩ 결과
run_simulation(circuit_id=..., shots=1024, noise_preset="high_noise") → 결과값 저하, |01⟩ 및 |10⟩ 발생
"이 회로를 실행해 줘: OPENQASM 2.0; include "qelib1.inc"; qreg q[2]; creg c[2]; h q[0]; cx q[0],q[1]; measure q -> c;"
Claude가 QASM 문자열을 파싱하여 동일한 시뮬레이션 파이프라인을 통해 실행합니다.
"이상적인 상태와 높은 노이즈 상태에서 GHZ 상태를 비교해 줘. 노이즈가 얽힘(entanglement)에 어떤 영향을 미치나요?"
src/quantum_mcp_demo/
├── server.py # MCP server entry point
├── circuits/
│ ├── presets.py # 5 named preset circuits
│ └── store.py # In-memory circuit storage (UUID-keyed)
├── tools/
│ ├── create_circuit.py # Tool: create from preset or QASM
│ ├── visualize.py # Tool: HTML diagram + gate JSON
│ └── simulate.py # Tool: AerSimulator + noise modeling
├── resources/
│ └── noise_presets.py # Resource: noise configuration list
├── prompts/
│ └── walkthrough.py # Prompt: guided simulation conversation
└── utils/
├── serialization.py # numpy → Python int conversion
└── errors.py # MCP error response builder사전 설정 | 큐비트 | 설명 | ||
| 2 | 얽힘 — ` | 00⟩ | 11⟩`이 50/50으로 분할 |
| 3 | 다중 큐비트 얽힘 | ||
| 1 | 하다마드 게이트를 통한 동일 중첩 | ||
| 3 | 양자 알고리즘 — 간섭 | ||
| 4 | 노이즈 스트레스 테스트 — 고정 시드 무작위 게이트 |
사전 설정 | 탈분극 p | 설명 |
| 없음 | 완벽한 시뮬레이션 |
| 0.001 | 현실적인 근거리 장치 |
| 0.01 | 강력한 노이즈 — 눈에 띄는 성능 저하 |
Claude Desktop에 망치 아이콘이 표시되지 않음
설정을 편집한 후 Claude Desktop을 완전히 종료하고 다시 실행하세요.
설정 JSON이 유효한지 확인하세요 (마지막 쉼표 금지).
Python 경로를 확인하세요: which python
python -m quantum_mcp_demo.server 실패
프로젝트 루트에서 pip install -e .를 실행했는지 확인하세요.
Python 버전을 확인하세요: python --version (3.13 이상 필요)
MCP Inspector 실행 시 포트 충돌
kill -9 $(lsof -t -i :6274) 2>/dev/null; kill -9 $(lsof -t -i :6277) 2>/dev/null시뮬레이션 결과가 예상과 다름
샷 횟수 불일치는 자동으로 감지되어 isError: true로 반환됩니다.
오류가 발생하면 shots를 줄여보세요 (예: 512).
Create a quantum circuit from a named preset or an OpenQASM 2.0 string. Provide exactly one of: preset (bell|ghz_3|superposition|deutsch_jozsa|random_4) or qasm.
| Name | Required | Description | Default |
|---|---|---|---|
| preset | No | ||
| qasm | No |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry full burden. It only states 'create', which implies mutation, but does not disclose side effects, permissions, rate limits, or whether the operation is reversible. Minimal behavioral context beyond the action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with purpose, and contains no unnecessary words. Every sentence adds value, making it highly concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that an output schema exists (implied), the description need not explain return values. It covers the essential parameter modes and preset list. However, it lacks error handling guidance (e.g., what happens if both or neither are provided) and interaction with sibling tools, but the description remains adequate for a simple creation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, so the description compensates by specifying that exactly one parameter must be provided and listing the preset options. It clarifies that qasm is an OpenQASM 2.0 string, adding semantic value. However, it does not detail the format or constraints further.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool creates a quantum circuit from a named preset or an OpenQASM 2.0 string, listing specific preset options. This distinguishes it from siblings (run_simulation, visualize_circuit) which perform different actions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for circuit creation but does not explicitly state when to use this tool over alternatives or provide exclusions. It lacks guidance on prerequisites or context for using presets versus QASM.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Run a stored circuit on AerSimulator with optional depolarizing noise. noise_preset: ideal | low_noise | high_noise. Returns counts, probabilities, metadata.
| Name | Required | Description | Default |
|---|---|---|---|
| circuit_id | Yes | ||
| shots | Yes | ||
| noise_preset | Yes |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions returns (counts, probabilities, metadata) but does not state whether the operation is read-only, has side effects, or requires specific permissions. The behavior is partially transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loads the core purpose, and presents noise options succinctly. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 3 required parameters, no annotations, and an output schema, the description covers the platform and noise but omits parameter constraints and fails to distinguish output structure beyond mentioning three fields. It is adequate but not rich.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description must compensate. It explains noise_preset with enumerated values, but leaves circuit_id and shots undocumented (no hint on circuit_id source or shots default/range). Only 1 of 3 parameters gains meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool runs a stored circuit on AerSimulator with optional noise, and the verb 'Run' paired with 'stored circuit' distinguishes it from sibling tools 'create_circuit' and 'visualize_circuit'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context (run a stored circuit) and provides specific noise preset options (ideal, low_noise, high_noise), but does not explicitly exclude alternatives or state prerequisites like needing a pre-existing circuit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Visualize a stored circuit as HTML and a structured gate list for narration.
| Name | Required | Description | Default |
|---|---|---|---|
| circuit_id | Yes |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral traits such as whether the operation is read-only, any side effects, or prerequisites (e.g., circuit must exist). This leaves uncertainty about its safety and failure modes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no unnecessary words. It front-loads the key action and outputs.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema and no annotations, the description is adequate but incomplete. It fails to specify error conditions, the format of the gate list, or prerequisite existence checks for the circuit.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'circuit_id' has 0% schema description coverage, and the description does not add any meaning beyond the schema's title. No guidance on what constitutes a valid circuit_id or how to obtain it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'visualize' and resource 'stored circuit', and specifies the output as HTML and a gate list for narration. This distinguishes it from siblings 'create_circuit' and 'run_simulation'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or when-not-to-use guidance is provided. Usage is implied by the context of having a stored circuit to visualize, but alternatives like run_simulation are not differentiated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
v0.1.0create_circuitrun_simulationvisualize_circuitScored across 3 tools
Each tool addresses a distinct phase of quantum circuit workflow: creation, simulation, and visualization. No overlap in functionality.
All tools follow a consistent verb_noun convention (create_circuit, run_simulation, visualize_circuit), making their purpose immediately clear.
Three tools cover the core lifecycle adequately. While more tools (e.g., list, delete) could be added, the current count is reasonable for a focused server.
The tools enable creating, running with noise, and visualizing circuits. Missing operations like listing or deleting circuits are minor gaps but do not severely hinder basic usage.
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