Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
제작자가 쓴 설명(영어 원문)
Build, compile, run and export FlagQuantum circuits locally. No credentials or outbound network.
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
FLAGQUANTUM_MCP_MAX_QUBITS, FLAGQUANTUM_MCP_MAX_GATES, FLAGQUANTUM_MCP_MAX_IR_BYTES필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"mcpServers": {
"flagquantum": {
"command": "uvx",
"args": [
"flagquantum-mcp-server"
],
"env": {
"FLAGQUANTUM_MCP_MAX_QUBITS": "your-value",
"FLAGQUANTUM_MCP_MAX_GATES": "your-value",
"FLAGQUANTUM_MCP_MAX_IR_BYTES": "your-value"
}
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add flagquantum --env FLAGQUANTUM_MCP_MAX_QUBITS=your-value --env FLAGQUANTUM_MCP_MAX_GATES=your-value --env FLAGQUANTUM_MCP_MAX_IR_BYTES=your-value -- uvx flagquantum-mcp-server실행하기 전에 빈 값을 채워 주세요.
프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"flagquantum": {
"command": "uvx",
"args": [
"flagquantum-mcp-server"
],
"env": {
"FLAGQUANTUM_MCP_MAX_QUBITS": "your-value",
"FLAGQUANTUM_MCP_MAX_GATES": "your-value",
"FLAGQUANTUM_MCP_MAX_IR_BYTES": "your-value"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"flagquantum": {
"type": "stdio",
"command": "uvx",
"args": [
"flagquantum-mcp-server"
],
"env": {
"FLAGQUANTUM_MCP_MAX_QUBITS": "your-value",
"FLAGQUANTUM_MCP_MAX_GATES": "your-value",
"FLAGQUANTUM_MCP_MAX_IR_BYTES": "your-value"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
FLAGQUANTUM_MCP_MAX_QUBITS envFLAGQUANTUM_MCP_MAX_GATES envFLAGQUANTUM_MCP_MAX_IR_BYTES env이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 6일 점검
레지스트리 이름이 GitHub 계정 FlagQuantum 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(0.3.2)은 10일 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Python (uv)도 있어야 해요.
같은 카테고리에는: Spec Driven Development, Remote Desktop Commander, dotnet-mcp
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
MCP server for .NET symbols, XAML, source generators, and restricted workspace edit
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
An MCP server that gives any MCP-compatible agent local access to the FlagQuantum SDK: build, compile, route, serialize and plan quantum circuits — and run them locally — with no credentials, no outbound network access and no hardware submission.
"Outbound" is the load-bearing word. Every tool here runs in this process and reaches nothing; the server never calls a provider, reads a token or submits a job. It can also *listen*, so a gateway that connects to its clients rather than launching them can reach it — see Serving over HTTP. An inbound listener is not egress.
Part of FlagQuantum/mcp-servers.
The mcp-name comment above is not decoration: the MCP Registry reads it from this README to verify that whoever publishes the registry entry also controls the PyPI package. Removing it breaks registry publishing.
Twenty-seven tools over stdio or Streamable HTTP. The research tools use the installed FlagQuantum service contract directly; the MCP layer does not reimplement request decoding, estimation, provider routing or scientific validation.
Build and inspect
| Tool | What it answers |
|---|---|
describe_gate_set_tool | Wire count, parameter names and aliases for named gates — or every gate |
analyze_circuit_tool | Gate counts, depth, wire usage, two-qubit gate count |
describe_layers_tool | Which gates run concurrently, and therefore where the depth comes from |
serialize_circuit_tool | Canonical IR JSON plus its content hash |
deserialize_circuit_tool | Is this IR valid, and does it round-trip unchanged? |
Parameters
| Tool | What it answers |
|---|---|
inspect_parameters_tool | Is this circuit parameterized, and where does each symbol sit? |
bind_parameters_tool | What does this ansatz look like once the symbols are numbers? |
Compile and route
| Tool | What it answers |
|---|---|
optimize_circuit_tool | What did target-independent optimization change? |
compile_circuit_tool | What circuit does the complete optimize-and-route pipeline produce? |
route_circuit_tool | What does this circuit cost on a line / ring / grid / custom topology? |
compare_topologies_tool | Which connectivity is cheapest for this circuit? |
describe_topology_tool | What is the connectivity, and how far apart are two wires? |
Export and present
| Tool | What it answers |
|---|---|
emit_openqasm_tool | OpenQASM 2.0 or 3.0 text |
import_openqasm_tool | FlagQuantum IR from OpenQASM text — the inverse of emit_openqasm_tool |
emit_qcis_tool | QCIS text |
draw_circuit_tool | An ASCII diagram of the circuit |
plan_execution_tool | How would the SDK execute this — which mode, device, how much memory? |
plan_evolution_tool | Validate and size a continuous-time Lindblad evolution without running it |
Run
| Tool | What it answers |
|---|---|
simulate_circuit_tool | Counts, samples, marginal probabilities or an expectation value from a local statevector run |
evolve_dynamics_tool | Time-resolved populations, observables and optional density matrices from local Lindblad evolution |
train_parameters_tool | The angles that lower a circuit's energy against a Pauli-sum Hamiltonian |
Research capability workflow
| Tool | What it answers |
|---|---|
search_capabilities_tool | Which approved local research operations match structured filters? |
describe_capability_tool | What exact request, result, limitations and validators does one operation declare? |
estimate_capability_tool | Is this request supported locally, and what bounded resources does FlagQuantum estimate? |
validate_capability_input_tool | Does the complete typed request pass upstream validation? |
execute_local_capability_tool | What Evidence Bundle results from explicit local provider execution? |
validate_evidence_tool | Is the returned Evidence Bundle intact and scientifically accepted by the named validator? |
Four concrete resources include flagquantum://version, flagquantum://gate-set, flagquantum://ir-schema, and the installed research catalog at flagquantum://capabilities/index. Two resource templates expose exact upstream documents without copying them: flagquantum://capabilities/{capability_id}/{version} and flagquantum://schemas/{schema_id}.
Three prompts: build_and_analyze_circuit, compile_for_topology, export_circuit.
These are recipes for the clients that present them to a person — Claude Desktop, the MCP Inspector, a host that turns them into slash commands. An autonomous agent may receive none of them: several recorded sessions could not enumerate them at all, and reported that they could not tell whether prompts existed. So nothing an agent has to know lives only here. Every constraint the prompts state is also in a tool summary, or in the server instructions, or in a resource — the QCIS refusal and the "say what you assumed" rule were the two exceptions, and they are in emit_qcis_tool and bind_parameters_tool now. PROMPT_CONSTRAINTS in tests/test_server_contract.py keeps that true.
pip install flagquantum-mcp-server
This pulls flagquantum, which depends on torch.
claude mcp add flagquantum -- uvx flagquantum-mcp-server
{
"mcpServers": { "flagquantum": { "command": "uvx", "args": ["flagquantum-mcp-server"] } } }
npx @modelcontextprotocol/inspector uvx flagquantum-mcp-server
A client that launches a process — Claude Code, Claude Desktop, the Inspector — uses the default stdio transport and needs nothing below. A client that instead *connects* to servers, such as a gateway holding several of them, needs the server to listen:
flagquantum-mcp-server --transport http --host 0.0.0.0 --port 8105 \
--allowed-host quantum-mcp:8105
The endpoint is /mcp on that host and port, and it speaks Streamable HTTP.
| Flag | Default | Meaning |
|---|---|---|
--transport | stdio | stdio or http. The default is unchanged, so nothing that already works needs editing |
--host | 127.0.0.1 | Interface to bind. Loopback by default: the server does not become reachable by accident |
--port | 8105 | Port to bind |
--allowed-host | none | A Host header the server will answer, repeatable |
--allowed-origin | none | A browser Origin the server will answer, repeatable |
Binding a non-loopback interface requires `--allowed-host`. Without it the server refuses to start rather than listen on every interface with nothing checking who reaches it:
$ flagquantum-mcp-server --transport http --host 0.0.0.0
usage: flagquantum-mcp-server [-h] ... flagquantum-mcp-server: error: --host 0.0.0.0 is not a loopback address, so the server would answer any Host header that reaches it. Name the hosts it should answer with --allowed-host HOST[:PORT], or bind 127.0.0.1.
Passing any --allowed-host or --allowed-origin turns host validation on; a request carrying an unlisted Host is answered 421 Misdirected Request. Loopback hosts are always answered, so enabling validation cannot lock out a local client.
Two things worth knowing if you are wiring this up:
Host is answered 200 with the keyword and 421 through the settings path.Two input formats are accepted, both of them FlagQuantum's own serialization.
`ir` (canonical) — FlagQuantum IR JSON, as produced by CircuitIR.to_json(). Versioned, hashable, and rejected if it carries unknown fields:
{
"kind": "flagquantum.circuit_ir", "version": "1.0", "n_wires": 2, "dtype": "complex64", "shape": [4], "instructions": [ {"opcode": "h", "wires": [0], "params": {}, "matrix": null, "metadata": {}}, {"opcode": "cx", "wires": [0, 1], "params": {}, "matrix": null, "metadata": {}} ], "observables": [], "measurements": [], "metadata": {} }
`qir` (convenience) — the compact gate list from Circuit.to_qir(), easier to write by hand:
[{"name": "h", "index": [0]}, {"name": "cx", "index": [0, 1]}]
A gate carries its arguments under `parameters`, which the example above never shows because neither gate takes one:
[{"name": "rz", "index": [0], "parameters": {"theta": 0.5}}]
The two formats use different key names, and this is the most common mistake: the gate list calls a gate name and its wires index, while serialized IR calls them opcode and wires. Sending IR keys as qir is rejected with a message that says so by name. An empty gate list is also rejected, because the wire count is inferred from the highest index — an empty list describes no circuit. A bare integer is accepted for a single-wire gate ("index": 0 means "index": [0]).
Either format can be passed to any tool; serialize_circuit_tool converts qir into canonical ir.
One more naming trap: an IR payload's version field is spelled `version`, and sending ir_version instead is rejected as an unknown key — but tool results report that same field as ir_version. The payload key and the reported key are not spelled the same way.
circuit_format is a closed set — the JSON schema publishes "enum": ["ir", "qir"], so a wrong value is rejected before any tool body runs. OpenQASM text is not a supported input. FlagQuantum ships emitters but no QASM parser, so there is nothing to convert it with; a caller holding OpenQASM has to load it into FlagQuantum itself and send the resulting IR.
A gate parameter is either a number or a symbol, and a symbol is written as a one-key object naming it:
{"name": "ry", "index": [0], "parameters": {"theta": {"$parameter": "theta"}}}
This works in both input formats. A symbol is what makes a circuit an ansatz: inspect_parameters_tool reports it, and bind_parameters_tool substitutes a number for it.
A bare string is not a symbol. {"theta": "theta"} is a value, not a reference; the SDK stores it as one, so the circuit reports itself as unparameterized. Nothing else complains: draw_circuit_tool prints the value it was handed, and a string prints as RY(theta) — indistinguishable from a real symbol — while plan_execution_tool plans the circuit for execution. So the input boundary rejects it, along with a misspelled marker ({"$unknown": ...}) and a non-string symbol name, naming the gate and the parameter. The other encodings a parameter may carry are $expression, $complex and $tensor; a mapping carrying none of those four keys is rejected for the same reason. The flagquantum://ir-schema resource carries a worked parameter_example.
One rough edge, inherited from the SDK: a *real* symbol is rendered as the SDK's repr of it, so RY(theta) appears as RY(Parameter(name='theta')). FlagQu
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