Quantum Expectations

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

• Connection: Runs in the cloud
• Transport: Streamable HTTP
• Category: Marketing & social media

Install

Pick the AI app you use, then copy the settings.

You need

• Runs in the cloudNothing to install; it connects over the internet

Which app do you use?

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

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

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

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

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

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These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Tool names and descriptions exactly as the server reported them on Nov 7, 2026. The maker wrote them, not us; we show them as plain text.

• compute_expectation

  Given a quantum circuit (2-qubit error rate p, qubit count n, depth d, optional connectivity class), compute the effective error rate, success probability, and optional surface-code or qLDPC overhead. Without error correction a 2d-lattice connectivity is charged as a routing mult

• compute_required_error_rate

  Inverse of compute_expectation. Given a circuit (numQubits, compDepth) and an acceptable effective error rate, return the required per-gate logical error rate (requiredLogicalErrorRatePerGate: a number, or null only when the target is genuinely unreachable; never 0) and, for ever

• compute_fault_tolerant_resources

  Given an algorithm stated as (numLogicalQubits, tCount) and a physical error rate (or hardwareId), derive the full surface-code + magic-state-distillation footprint from the general laws of the Litinski lattice-surgery cost model (no per-scenario constants): distillation factory

• compare_hardware_scenarios

  Run the same circuit against multiple current SOTA hardware entries in one call so an agent can rank platforms without N sequential compute_expectation calls. Defaults to every entry in list_current_quantum_computers when hardwareIds is omitted.

• list_current_quantum_computers

  Return the representative-entry table of current SOTA quantum computers (id, hardware type, physical qubit count, 2-qubit error rate, connectivity class with a note on the coupling graph, source URL). Same data that powers the website's "Current Quantum Computers" table. For the

• list_quops_scores

  Return the measured QUOPS (quantum universal operation performance system, a cross-platform capability benchmark) scores (arXiv:2609.12146): per device, the largest random universal circuit size executed at polarization >= 1/sqrt(e) inside the cone w^2 <= s <= w^3, with width, QU

• list_hardware_timings

  Return per-platform gate-cycle timings (2Q gate time, readout time, in SI seconds) plus the testbed they were measured on (`representativeDevice`) and the native 2Q gate name, with source URLs. Joins list_current_quantum_computers via `hardwareType`, but the numbers are BEST-CASE

• compute_quantum_volume_rate

  Compute the Quantum Volume Rate (QV/second): QVR = V_Q / (log2(V_Q) * t_2Q + t_meas). First-order estimate of how fast a device prepares one QV-sized square circuit (one native 2Q gate per QV layer + one end-of-circuit measurement). OVERSTATES achievable rate: real compilation in

• fit_historic_series

  Fit a log-linear trend (ln(value) = slope * year + intercept) to one historic series — fidelity or qubit-count — for one hardware type. Atomic primitive: compose with list_current_quantum_computers, compute_required_error_rate, or your own modelling to answer "when might hardware

• list_example_algorithms

  Return the curated list of example quantum algorithms with published resource estimates (qubit count, depth/gate count, source paper URL). Useful for comparing what algorithms need vs. what hardware can deliver. Each entry carries a `provenance` field: 'published-circuit' means t

• list_qldpc_codes

  Return the catalog of supported qLDPC (quantum low-density parity-check) error-correction codes (id, label, family, n, k, d, circuitLevelDistance, ancilla counts, roundsPerLogicalOp, threshold, fitCoefficients {c0, c1, c2}, logicalErrorExponent [alpha = d_circ/2], source URLs, pr

• get_historic_series

  Return the full historic time series — either two-qubit gate error rates ("fidelity") or physical qubit counts ("qubit-count") — broken down by hardware type. Each datapoint carries a source URL. Use this to extrapolate trends — "when might hardware reach X?" — or pair with fit_h

• get_agent_brief

  Return the plain-text site brief describing scope, assumptions, the honesty clause, and the API contract. Mirrors the /agent.txt document served by the website.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

• ! Caution

  Maker matches the repo

  The registry lists no source repo, so we cannot match the publisher (quantum-expectations.com) to the code

• … Not checked yet

  Still maintained

  We have not read this repo from GitHub yet

• … Not checked yet

  Has a licence

  We have not read this repo from GitHub yet

• ✓ Pass

  Endpoint responds

  Responded in 130 ms (HTTP 200)

• – Not applicable

  Sign-in with OAuth

  No sign-in needed

• ✓ Pass

  No hidden instructions in tool descriptions

  Read 13 tool descriptions and found no hidden instructions to the AI

Compared with others in Marketing & social mediai

• More stars than 0% of the other 3563 servers in this category
• Published to the registry more recently than 75% of the other 3563 servers in this category
• Basic checks equal to or better than 50% of the other 3563 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

README from the maker

No README found in the repo