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FlagQuantum MCP Server

de FlagQuantumversión 0.3.2i★ –iSe ejecuta en tu computadora
Nombre en el registroio.github.FlagQuantum/flagquantum-mcp-server

Instalar

Resumen

Descripción del creador (original en inglés)

Build, compile, run and export FlagQuantum circuits locally. No credentials or outbound network.

Los tres pilares de PopNx MCP

Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.

Qué puedes hacer con él

Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.

  • Conexión: Se ejecuta en tu computadora
  • Transporte: stdio
  • Categoría: Otros

Instalación

Elige la app de IA que usas y copia la configuración.

Antes de instalar

  • Revisiones básicas: 1 de 1 superadas
  • Se ejecuta en tu computadora con los permisos de tu usuario (archivos, red, apps).
  • Debes completar tú: FLAGQUANTUM_MCP_MAX_QUBITS, FLAGQUANTUM_MCP_MAX_GATES, FLAGQUANTUM_MCP_MAX_IR_BYTES

Necesitas

  • PyPIuv de Python instalado (para el comando uvx)

¿Qué app usas?

Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.

Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json

{
  "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"
      }
    }
  }
}

Ejecuta esto en tu terminal

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-server

Completa los valores vacíos antes de ejecutarlo.

Abrir en Cursor

O copia la configuración tú

Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json

{
  "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"
      }
    }
  }
}

Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.

Abrir en VS Code

O copia la configuración tú

Pégalo en .vscode/mcp.json de tu proyecto

{
  "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"
      }
    }
  }
}

Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.

Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.

Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.

Valores que debes completar

  • FLAGQUANTUM_MCP_MAX_QUBITS env
    Largest circuit width the server will process. Defaults to 24.
  • FLAGQUANTUM_MCP_MAX_GATES env
    Largest instruction count the server will process. Defaults to 10000.
  • FLAGQUANTUM_MCP_MAX_IR_BYTES env
    Largest serialized circuit payload accepted, in bytes. Defaults to 262144.

Esta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.

Qué puede hacer

Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.

Revisiones básicasi

Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 6 nov 2026

  • ✓ Superada

    El creador coincide con el repo

    El nombre en el registro se verificó con la cuenta de GitHub FlagQuantum, dueña del repo

  • … Aún sin revisar

    Sigue en mantenimiento

    Todavía no hemos leído este repo en GitHub

  • … Aún sin revisar

    Tiene licencia

    Todavía no hemos leído este repo en GitHub

  • – No aplica

    El endpoint responde

    Este se ejecuta en tu computadora; no hay endpoint en internet

  • – No aplica

    Inicio de sesión con OAuth

    Se ejecuta en tu computadora y usa ajustes locales en su lugar

  • … Aún sin revisar

    Sin instrucciones ocultas en las descripciones de herramientas

    Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet

Comparado con otros en Otrosi

  • Más estrellas que el 0% de los otros 32398 servidores de esta categoría
  • Publicado en el registro más recientemente que el 77% de los otros 32398 servidores de esta categoría
  • Revisiones básicas iguales o mejores que el 100% de los otros 32398 servidores de esta categoría

Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.

Preguntas frecuentes

¿Es seguro FlagQuantum MCP Server?

Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.

¿Qué claves o códigos necesita?

El registro no indica ninguna clave obligatoria, aunque algunos servidores te piden iniciar sesión la primera vez que los usas.

¿Se ejecuta en mi computadora o en la nube?

Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).

¿Sigue en mantenimiento?

El repo de GitHub cambió por última vez –, y la última versión (0.3.2) llegó al registro hace 10 días.

¿Qué apps pueden usarlo?

Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Python (uv) en tu computadora.

¿Qué puedo usar en su lugar?

En la misma categoría: Spec Driven Development, Remote Desktop Commander, AI Deprecations

Alternativas

Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.

Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi

Spec Driven Development

de formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

Se ejecuta en tu computadora★ 440MITActualizado hace 14 meses
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Remote Desktop Commander

de desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

Se ejecuta en la nube★ 211Actualizado ayer
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AI Deprecations

de aideprecations.com

AI model shutdown dates, replacements, change feed and webhook alerts for 8 providers.

Se ejecuta en la nubeActualizado hoy
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README del creador

Abrir el README

Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.

FlagQuantum MCP Server

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.

What it does

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

ToolWhat it answers
describe_gate_set_toolWire count, parameter names and aliases for named gates — or every gate
analyze_circuit_toolGate counts, depth, wire usage, two-qubit gate count
describe_layers_toolWhich gates run concurrently, and therefore where the depth comes from
serialize_circuit_toolCanonical IR JSON plus its content hash
deserialize_circuit_toolIs this IR valid, and does it round-trip unchanged?

Parameters

ToolWhat it answers
inspect_parameters_toolIs this circuit parameterized, and where does each symbol sit?
bind_parameters_toolWhat does this ansatz look like once the symbols are numbers?

Compile and route

ToolWhat it answers
optimize_circuit_toolWhat did target-independent optimization change?
compile_circuit_toolWhat circuit does the complete optimize-and-route pipeline produce?
route_circuit_toolWhat does this circuit cost on a line / ring / grid / custom topology?
compare_topologies_toolWhich connectivity is cheapest for this circuit?
describe_topology_toolWhat is the connectivity, and how far apart are two wires?

Export and present

ToolWhat it answers
emit_openqasm_toolOpenQASM 2.0 or 3.0 text
import_openqasm_toolFlagQuantum IR from OpenQASM text — the inverse of emit_openqasm_tool
emit_qcis_toolQCIS text
draw_circuit_toolAn ASCII diagram of the circuit
plan_execution_toolHow would the SDK execute this — which mode, device, how much memory?
plan_evolution_toolValidate and size a continuous-time Lindblad evolution without running it

Run

ToolWhat it answers
simulate_circuit_toolCounts, samples, marginal probabilities or an expectation value from a local statevector run
evolve_dynamics_toolTime-resolved populations, observables and optional density matrices from local Lindblad evolution
train_parameters_toolThe angles that lower a circuit's energy against a Pauli-sum Hamiltonian

Research capability workflow

ToolWhat it answers
search_capabilities_toolWhich approved local research operations match structured filters?
describe_capability_toolWhat exact request, result, limitations and validators does one operation declare?
estimate_capability_toolIs this request supported locally, and what bounded resources does FlagQuantum estimate?
validate_capability_input_toolDoes the complete typed request pass upstream validation?
execute_local_capability_toolWhat Evidence Bundle results from explicit local provider execution?
validate_evidence_toolIs 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.

Install

pip install flagquantum-mcp-server

This pulls flagquantum, which depends on torch.

Claude Code
claude mcp add flagquantum -- uvx flagquantum-mcp-server
Claude Desktop / Cline
{

"mcpServers": { "flagquantum": { "command": "uvx", "args": ["flagquantum-mcp-server"] } } }

MCP Inspector
npx @modelcontextprotocol/inspector uvx flagquantum-mcp-server
Serving over HTTP

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.

FlagDefaultMeaning
--transportstdiostdio or http. The default is unchanged, so nothing that already works needs editing
--host127.0.0.1Interface to bind. Loopback by default: the server does not become reachable by accident
--port8105Port to bind
--allowed-hostnoneA Host header the server will answer, repeatable
--allowed-originnoneA 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:

  • Configure validation through the settings object, not `http_app( allowed_hosts=...)`. That keyword appends to a list which is only consulted once validation is on, so on its own it reads as a security setting and enforces nothing. Measured on fastmcp 3.4.7: a bogus Host is answered 200 with the keyword and 421 through the settings path.
  • `--transport http` adds an inbound socket, not an outbound one. No tool gains a network path; rule 4 in AGENTS.md is unchanged.

Circuit formats

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.

On parameters

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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