Use MCP

Connect the calculator to your AI assistant as a native tool. Add the URL once — no API key, no bootstrap fetch, no JSON-parsing boilerplate.

Connect your AI assistant

This site also runs a Model Context Protocol server. The compute tool, historic hardware data, and curated algorithm list become native tools your assistant can call directly.

Endpoint

https://www.quantum-expectations.com/api/mcp

Streamable HTTP · Stateless sessions · CORS open · Rate-limited per IP

One-click install

Add to Claude Cursor VS Code LM Studio Goose

Each opens the client's add-connector dialog pre-filled — you confirm before anything is added.

Claude Desktop / Cursor / Windsurf

Add to your MCP config file:

{
  "mcpServers": {
    "quantum-expectations": {
      "type": "http",
      "url": "https://www.quantum-expectations.com/api/mcp"
    }
  }
}

Claude Desktop: ~/Library/Application Support/Claude/claude_desktop_config.json on macOS. Restart the client after saving.

Claude Code CLI

One command:

claude mcp add --transport http quantum-expectations https://www.quantum-expectations.com/api/mcp

ChatGPT

Settings → Connectors → Add custom connector, then paste the endpoint URL above.

Stdio-only clients

Bridge through mcp-remote:

{
  "command": "npx",
  "args": ["-y", "mcp-remote", "https://www.quantum-expectations.com/api/mcp"]
}

What you get

compute_expectation — effective error rate, success probability, and surface-code / qLDPC overhead for a given circuit (error rate, qubit count, depth).
compute_required_error_rate — inverse: given a circuit and an acceptable error budget, what physical error rate does the hardware need to achieve?
compute_fault_tolerant_resources — full fault-tolerant footprint for an algorithm (logical qubits + T count): distillation factory, code distance, physical qubits, and wall-clock time from the Litinski cost model, under two published logical-error fits.
compare_hardware_scenarios — run the same circuit against all current hardware platforms in one call and rank them.
fit_historic_series — fit a log-linear trend to the error-rate or qubit-count history and extrapolate when hardware might reach a target value.
compute_quantum_volume_rate — first-order QV/second estimate for a hardware configuration.
list_current_quantum_computers, list_hardware_timings, list_example_algorithms, list_qldpc_codes — reference tables (same data as on this site, plus gate-cycle timings not shown on the homepage).
get_historic_series — full time series with source URLs for trend extrapolation. Pass seriesType as "fidelity" or "qubit-count".
get_agent_brief — scope, assumptions, and honesty clause.
Prompts (slash commands in supporting clients): assess_feasibility, assess_fault_tolerant_feasibility, compare_platforms — guided analyses your assistant performs itself with the tools above, assumptions stated.

More tools coming soon.

Try it

Once connected, ask your assistant to do analyses, e.g.:

← Back · /agent.txt