Quantum Engineer Plugin

Overview

This is an enterprise-grade feature available exclusively to Classiq’s enterprise customers.

The Quantum Engineer plugin brings Classiq expertise directly into your AI-powered IDE. It teaches coding agents like Claude Code, Cursor, and Codex how to model, synthesize, execute, analyze, and post-process quantum programs with Classiq. Build, run, and analyze quantum programs in natural language — describe what you want and the agent handles every step, from writing the model to reading back results. Programs are expressed in Qmod, and draw on the open library of reusable quantum functions. Synthesis delegates to Classiq’s backend engine, which compiles high-level models into hardware-optimized circuits automatically. The plugin includes skills for each phase of quantum development:

Modeling — write quantum algorithms in Python using Classiq.
Synthesis — compile a model into a quantum program with synthesize(), constraints, and hardware targets.
Execution — run circuits: sample, observe, calculate_state_vector, and variational loops.
Post-processing — interpret results: histograms, energy curves, and most-probable states.
Analyzer — inspect synthesized programs for gate counts, depth, and hardware fit.
Qiskit migration — translate existing Qiskit code into Classiq models.

A built-in reference layer keeps the agent’s knowledge current as it works.

Installation

The marketplace is access-controlled: reach out to Classiq to get onboarded, and you’ll receive a personal GitHub invitation to the repository. Accept it first — the steps below assume you already have access.

Claude Code
Cursor

Add the marketplace once per machine, using the repository from your invitation:

/plugin marketplace add <owner>/<repo>

Then install the plugin:

/plugin install classiq-quantum-engineer@classiq

Restart Claude Code after the first install so the bundled MCP server comes up. You’ll be prompted to approve the classiq-mcp server on first use.Keeping it up to date:

/plugin marketplace update classiq        # pull the latest catalog
/plugin update classiq-quantum-engineer@classiq   # update the plugin
/plugin list                              # see what you have installed

The plugin requires the classiq Python package in your project’s environment. If you don’t have it yet, ask the agent to install it — see the Install Classiq example in the Examples section below, or Use Python and Classiq for manual SDK setup.

Usage

Once installed, just describe what you want in natural language — no special syntax required. The agent picks the right skill for each phase of the work:

You ask for	Skill that responds
Writing, editing, or debugging a quantum algorithm in Python (`@qfunc`, `QBit`, `QNum`, `QArray`)	Modeling
Writing or debugging native Qmod (`.qmod` files)	Native Qmod
Compiling a model — `synthesize()`, constraints, hardware targets	Synthesis
Running a circuit — `sample`, `observe`, `calculate_state_vector`, variational loops	Execution
Interpreting results — histograms, energy curves, most-probable states	Post-processing
Inspecting a synthesized program — gate counts, depth, hardware fit	Analyzer
Translating Qiskit code into Classiq models	Qiskit migration

For requests that span multiple phases — “model this and run it” — the agent organizes the full pipeline end-to-end.

Examples

Hello World
Quantum Arithmetic
Grover's Search
Install Classiq

Prompt:

Create a Bell state, synthesize it, run it on the simulator, and show the measurement counts.

Generated code:

from classiq import *

@qfunc
def main(res: Output[QArray[QBit, 2]]):
    allocate(2, res)
    H(res[0])
    CX(res[0], res[1])

qprog = synthesize(main)
result = sample(qprog)
print(result)

Output:

      res  counts  probability bitstring
0  [1, 1]    1036     0.505859        11
1  [0, 0]    1012     0.494141        00

Prompt:

Write a quantum program that puts a 1-qubit integer in superposition, assigns 2 to a second integer, computes their sum, and runs it.

Generated code:

from classiq import *

@qfunc
def main(x: Output[QNum], y: Output[QNum], z: Output[QNum]):
    allocate(1, x)
    H(x)
    y |= 2
    z |= x + y

qprog = synthesize(main)
res = sample(qprog)
print(res)

Output:

x	y	z	counts	probability
0	2	2	1049	0.512
1	2	3	999	0.488

Prompt:

Use Grover's algorithm to find all pairs (x, y) of 2-bit integers where x + y < 4 and (x * y) % 4 == 2. Run it and show which states get amplified.

Generated code:

from classiq import *

VAR_SIZE = 2

class GroverVars(QStruct):
    x: QNum[VAR_SIZE]
    y: QNum[VAR_SIZE]

@qperm
def my_predicate(vars: Const[GroverVars], res: QBit) -> None:
    res ^= (vars.x + vars.y < 4) & ((vars.x * vars.y) % 4 == 2)

@qfunc
def main(vars: Output[GroverVars]):
    allocate(vars)
    hadamard_transform(vars)
    power(
        2,
        lambda: grover_operator(
            lambda vars: phase_oracle(predicate=my_predicate, target=vars),
            hadamard_transform,
            vars,
        ),
    )

qprog = synthesize(main)
result = sample(qprog)
result

Output:

vars.x	vars.y	probability
1	2	0.481
2	1	0.463
2	2	0.006

Prompt:

Install classiq and set it up for me.

The agent invokes the Setup skill, which walks through the full installation in your environment: it runs an environment diagnostic, installs the classiq package via pip, opens a browser window for authentication, and confirms everything is ready with a final status summary.

claude code completing the classiq installation using quantum engineer plugin

Per-project best practices

A small amount of one-time setup per project pays off quickly: a project memory file gives the agent persistent context about your environment, sanity checks let you verify everything is wired up before you start, and a troubleshooting reference saves time when something unexpected happens.

Memory file

Both IDEs support a project-level file that the agent reads at the start of every conversation. Use it to record your Python environment and any project-specific conventions — so the agent never has to ask and never guesses wrong.

Claude Code
Cursor

Create CLAUDE.md at the root of your project and fill in the bracketed fields:

# [Project Name]

## Environment

- Python: [path/to/venv/bin/python]  <!-- or just `python3` if using the system default -->
- Classiq SDK: installed in the environment above

## Backend

Default: Classiq cloud simulator.
[Optional: list hardware targets or execution preferences for this project.]

## Project overview

[One or two sentences describing the quantum algorithms or application this project implements.]

## Conventions

[Any project-specific patterns — naming, file layout, preferred synthesis constraints, etc.]

Claude Code picks up CLAUDE.md automatically — no additional configuration required.

Create .cursor/rules/classiq.mdc at the root of your project. This file gives Cursor persistent Classiq-specific context for the project.

---
description: Classiq project context
alwaysApply: true
---

# [Project Name]

## Environment

- Python: [path/to/venv/bin/python]  <!-- or just `python3` if using the system default -->
- Classiq SDK: installed in the environment above

## Backend

Default: Classiq cloud simulator.
[Optional: list hardware targets or execution preferences for this project.]

## Project overview

[One or two sentences describing the quantum algorithms or application this project implements.]

## Conventions

[Any project-specific patterns — naming, file layout, preferred synthesis constraints, etc.]

The alwaysApply: true frontmatter tells Cursor to load this rule for every conversation in the project.To verify the rule is active, open Settings → Rules and confirm the project rule appears. You can also ask the agent: “What Classiq project context do you see?” The response should reflect the environment and conventions from .cursor/rules/classiq.mdc.

Sanity checks

Run these checks after installation to confirm the plugin is wired up correctly.

Claude Code
Cursor

Verify the plugin is installed:

/plugin list

Look for classiq-quantum-engineer@classiq in the output. If it is missing, reinstall:

/plugin install classiq-quantum-engineer@classiq

Confirm skills are active:Run /status or ask the agent directly: "Which Classiq skills do you have loaded?" The response should name skills such as classiq-modeling, classiq-synthesis, and classiq-execution.Confirm the MCP server is running:Ask the agent:

"Can you look up the Classiq docs for synthesize?"

A successful lookup means the classiq-mcp server is up. A timeout or “no tools available” reply means the server did not start — see Troubleshooting below.

Verify the plugin is installed:

Open Cursor Settings → Plugins.

The classiq-quantum-engineer plugin should appear with status Imported. If it is missing, re-import it from the GitHub URL in your invitation. If import fails, confirm that you accepted the GitHub invitation and are signed into Cursor with an account that can access the repository.Confirm skills are active:

Go to Settings → Rules → Agent Decides.

You should see skills such as classiq, classiq-modeling, classiq-synthesis, and classiq-execution.You can also ask the agent:

Which Classiq skills do you have loaded?

A successful response should name the Classiq skills available to the agent.Confirm the MCP server is running:

Go to Settings → Features → Model Context Protocol and confirm Classiq Docs is enabled.

Then ask the agent:

Can you look up the Classiq docs for synthesize?

A successful lookup confirms the MCP server is running. A timeout, missing-tool message, or generic answer without a docs lookup usually means the MCP server did not start correctly.Confirm the SDK is available in the project environment:Ask the agent:

Check whether the classiq Python package is installed in this project environment.

If the package is missing, you can ask the agent to install it.

Troubleshooting

MCP server does not start

Claude Code
Cursor

The classiq-mcp server starts automatically on launch, but requires a one-time approval prompt on first use.

Run /plugin list — confirm classiq-quantum-engineer@classiq appears.
Go to Settings → MCP Servers. If classiq-mcp shows as disabled, enable it.
Restart Claude Code. The server starts fresh on each launch.

If the server still does not appear after a restart, try reinstalling:

/plugin update classiq-quantum-engineer@classiq

Skills do not load

Claude Code
Cursor

Skills appear in Settings → Rules. If they are absent after installation:

Quit and relaunch Claude Code.
Confirm the plugin installed cleanly: /plugin list should show classiq-quantum-engineer@classiq without an error flag.

Plugin is installed but not updating

Claude Code
Cursor

If synthesize behavior or skill instructions seem outdated:

/plugin marketplace update classiq   # pull the latest catalog
/plugin update classiq-quantum-engineer@classiq

Restart Claude Code after updating.

AI

Authentication

Modeling

Synthesis

Execution

Analysis

Studio

Applications

Quantum Engineer Plugin

Overview

Installation

Usage

Examples

Per-project best practices

Memory file

Sanity checks

Troubleshooting

MCP server does not start

Skills do not load

Plugin is installed but not updating

See also

​Overview

​Installation

​Usage

​Examples

​Per-project best practices

​Memory file

​Sanity checks

​Troubleshooting

​MCP server does not start

​Skills do not load

​Plugin is installed but not updating

​See also

Overview

Installation

Usage

Examples

Per-project best practices

Memory file

Sanity checks

Troubleshooting

MCP server does not start

Skills do not load

Plugin is installed but not updating

See also