stim-mcp-server 0.1.5

MCP server exposing Google's Stim quantum stabilizer circuit library as LLM tools

stim-mcp-server

MCP server wrapping Google's Stim stabilizer circuit simulator. Wire it up to an LLM and you can build and sample circuits through conversation.

This is an experimental tool for exploration and is in a beta phase. It should be treated as such.

Tools

Tool	Description
hello_quantum	Health check — returns Stim version and active session count
create_circuit	Validate a Stim circuit string and open a persistent session
append_operation	Append one or more Stim instructions to an existing circuit
sample_circuit	Simulate a circuit and return measurement statistics
analyze_errors	Build the Detector Error Model and find shortest logical error paths
get_circuit_diagram	Return an ASCII, SVG, or timeline diagram
inject_noise	Add depolarizing or X error noise to a circuit
generate_circuit	Generate standard QEC circuits (surface, repetition, color codes)

Connecting to the remote server

A hosted instance runs on Google Cloud Run:

URL: https://stim-mcp-5s3woqufqa-uc.a.run.app/mcp Transport: Streamable HTTP (MCP 1.x)

Claude.ai

Go to Settings → Connectors → Go To Customize → Tap the "+" icon → Add custom connector and the name "Stim" the URL above.

Claude Code (CLI)

Add to your ~/.claude/claude.json (or project-level .claude/claude.json):

{
  "mcpServers": {
    "stim-mcp": {
      "url": "https://stim-mcp-5s3woqufqa-uc.a.run.app/mcp"
    }
  }
}

Other MCP clients

Use POST https://stim-mcp-5s3woqufqa-uc.a.run.app/mcp with Content-Type: application/json and Accept: application/json, text/event-stream.

Cold start: The server scales to zero when idle. The first request after a period of inactivity may take 5–10 seconds. In-memory circuit sessions are lost on scale-down — circuits are cheap to recreate.

Installation

Needs uv.

Via PyPI (recommended)

No cloning needed. Configure your MCP client (see below) and uvx handles the rest on first run.

From source (development)

git clone https://github.com/DeDuckProject/stim-mcp
cd stim-mcp
uv sync

Running locally

Claude Desktop

macOS — ~/Library/Application Support/Claude/claude_desktop_config.json Windows — %APPDATA%\Claude\claude_desktop_config.json Linux — ~/.config/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "stim": {
      "command": "/path/to/uvx",
      "args": ["--from", "stim-mcp-server", "stim-mcp-server"]
    }
  }
}

Replace /path/to/uvx with the output of which uvx.

Claude Code

claude mcp add stim -- /path/to/uvx --from stim-mcp-server stim-mcp-server

Replace /path/to/uvx with the output of which uvx.

From source (development)

claude mcp add stim -- /path/to/uv run --directory /path/to/stim-mcp stim-mcp-server

Stdio (direct)

uv run stim-mcp-server

HTTP / SSE (local testing)

MCP_TRANSPORT=sse stim-mcp-server
# Server listens on http://localhost:8080/mcp

Inspect with the MCP inspector:

npx @modelcontextprotocol/inspector http://localhost:8080/mcp

Docker

docker build -t stim-mcp .
docker run -p 8080:8080 stim-mcp
# Server listens on http://localhost:8080/mcp

MCP dev tools

uv run mcp dev src/stim_mcp_server/server.py

Deploying to Cloud Run

Prerequisites

brew install --cask google-cloud-sdk
gcloud auth login
gcloud config set project YOUR_PROJECT_ID
gcloud services enable run.googleapis.com artifactregistry.googleapis.com cloudbuild.googleapis.com

Deploy

gcloud run deploy stim-mcp \
  --source . \
  --region us-central1 \
  --allow-unauthenticated \
  --port 8080 \
  --memory 512Mi \
  --cpu 1 \
  --min-instances 0 \
  --max-instances 1

--source . triggers Cloud Build to build the Docker image — no local Docker required. --max-instances 1 keeps circuit sessions consistent (in-memory store). --min-instances 0 enables scale-to-zero.

Environment variables

Variable	Default	Description
MCP_TRANSPORT	stdio	Set to anything else (e.g. sse) to start the HTTP server
MCP_HOST	0.0.0.0	Bind address for HTTP mode
MCP_PORT	8080	Port for HTTP mode

Privacy & Security

Circuit IDs are 128-bit random tokens (UUID v4), making them practically impossible to guess. However, the shared server has no authentication and no access control — anyone who obtains a circuit ID can read and modify that circuit.

If you care about the privacy of your circuits, run the MCP server locally (see Running locally). The remote server is intended for experimentation and learning, not sensitive work.

Tool invocations on the remote server are logged anonymously (tool name only, no arguments or circuit data) for usage analytics.

Examples

"Create a Bell state and sample it 1000 times"

"What's the shortest error path in this surface code?"

"Add 0.1% depolarizing noise and show me what changes"

Development

uv sync
uv run pytest

Releasing

Pushing a v* tag to master triggers the full release pipeline (tests must pass first):

• PyPI — package is built and published automatically
• Cloud Run — server is deployed automatically

# bump version in pyproject.toml, then:
git tag v0.x.y
git push origin v0.x.y

Required GitHub secrets: PYPI_API_TOKEN, GCP_SA_KEY.