# Quantum Expectations MCP server

Quantum error-correction feasibility: success probability, qubit overhead, records, trends.

## Links
- Registry page: https://www.getdrio.com/mcp/com-quantum-expectations-quantum-expectations
- Website: https://www.quantum-expectations.com

## Install
- Endpoint: https://www.quantum-expectations.com/api/mcp
- Auth: Not captured

## Setup notes
- Remote endpoint: https://www.quantum-expectations.com/api/mcp

## Tools
- compute_expectation (Compute Quantum Expectation) - Given a quantum circuit (2-qubit error rate p, qubit count n, depth d), compute the effective error rate, success probability, and optional surface-code or qLDPC overhead. The response is self-describing (formulas, assumptions, caveats, glossary, SOTA hardware, historic series with source URLs) so an agent can reason from one call. For the inverse ("what hardware do I need?") use compute_required_error_rate; to rank multiple platforms in one call use compare_hardware_scenarios. Endpoint: https://www.quantum-expectations.com/api/mcp
- compute_required_error_rate (Compute Required Error Rate (Inverse)) - Inverse of compute_expectation. Given a circuit (numQubits, compDepth) and an acceptable effective error rate, return the required per-gate logical error rate and, for every EC option (no-EC, surface-code per distance, every qLDPC code), the required physical error rate plus the subset of current SOTA hardware that already qualifies. Answers "what hardware do I need to run this algorithm?". Endpoint: https://www.quantum-expectations.com/api/mcp
- compute_fault_tolerant_resources (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 choice, tile layout, required code distance, total physical qubits, and wall-clock time. Results are reported under TWO published logical-error fits (conservative + optimistic) because they disagree by 13-268x (d=7 to d=25) - always state both. Returns an explicit `infeasible` block when no cataloged factory or code distance can satisfy the error budget. Computes numbers only: comparing against classical alternatives and concluding "should this run on a quantum computer" stays with you, the calling agent (state the caveats when you do). Endpoint: https://www.quantum-expectations.com/api/mcp
- compare_hardware_scenarios (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. Endpoint: https://www.quantum-expectations.com/api/mcp
- list_current_quantum_computers (Current Quantum Computers) - Return the representative-entry table of current SOTA quantum computers (id, hardware type, physical qubit count, 2-qubit error rate). Same data that powers the website's "Current Quantum Computers" table. Endpoint: https://www.quantum-expectations.com/api/mcp
- list_hardware_timings (Hardware Gate-Cycle Timings) - Return per-platform gate-cycle timings (2Q gate time, readout time, in SI seconds) plus the representative device and native 2Q gate name, with source URLs. Joins list_current_quantum_computers via `hardwareType`. Use for runtime estimates, ratio analysis, or as inputs to compute_quantum_volume_rate. Values are representative current-generation numbers, not records. Endpoint: https://www.quantum-expectations.com/api/mcp
- compute_quantum_volume_rate (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 inflates the 2Q-gate count per layer; omits reset/SPAM, mid-circuit measurement, and classical-control latency. For a production throughput metric, see IBM's CLOPS (arXiv:2110.14108). Endpoint: https://www.quantum-expectations.com/api/mcp
- fit_historic_series (Fit Historic Series (log-linear)) - 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 reach X?". residualStdDev is the BIASED (maximum-likelihood) RMS — divides by n, not (n - 2); on small series (n ≈ 3–5) inflate by √(n / (n - 2)) before building confidence intervals. Endpoint: https://www.quantum-expectations.com/api/mcp
- list_example_algorithms (Example Quantum 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. Endpoint: https://www.quantum-expectations.com/api/mcp
- list_qldpc_codes (qLDPC Code Catalog) - Return the catalog of supported qLDPC codes (id, label, family, n, k, d, circuitLevelDistance, ancilla counts, roundsPerLogicalOp, threshold, prefactor [per block per syndrome cycle], logicalErrorExponent [= d_circ/2], source URLs). Use a code's `id` as the `errorCorrectionCode` input to `compute_expectation`. Endpoint: https://www.quantum-expectations.com/api/mcp
- get_historic_series (Historic Hardware Series (Fidelity or Qubit Count)) - 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_historic_series for a log-linear fit on one hardware type. Endpoint: https://www.quantum-expectations.com/api/mcp
- get_agent_brief (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. Endpoint: https://www.quantum-expectations.com/api/mcp

## Resources
- resource://quantum-expectations/historic-fidelity - Historic 2-Qubit Gate Fidelity Historic 2-qubit gate error rates by hardware type (with source URLs). MIME type: application/json
- resource://quantum-expectations/historic-qubit-count - Historic Physical Qubit Counts Historic physical qubit counts by hardware type (with source URLs). MIME type: application/json
- resource://quantum-expectations/current-quantum-computers - Current Quantum Computers Representative-entry table of current SOTA quantum computers. MIME type: application/json
- resource://quantum-expectations/hardware-timings - Hardware Gate-Cycle Timings Per-platform 2-qubit gate time and readout time (SI seconds) with source URLs. Joins with current-quantum-computers via hardwareType. MIME type: application/json
- resource://quantum-expectations/example-algorithms - Example Quantum Algorithms Curated list of quantum algorithms with published resource estimates. MIME type: application/json
- resource://quantum-expectations/qldpc-codes - qLDPC Code Catalog Supported qLDPC codes with thresholds and source URLs. MIME type: application/json
- resource://quantum-expectations/agent-brief - Agent Brief Plain-text site brief with scope, assumptions, honesty clause, and API contract. MIME type: text/plain

## Prompts
- assess_feasibility - Assess Feasibility of a Quantum Circuit Guided analysis: when could a circuit (logical qubits × depth, target error budget) become feasible on real hardware? Composes compute_required_error_rate and fit_historic_series; the agent draws the conclusions and states every assumption. Arguments: numQubits, compDepth, acceptableErrorRatePercent
- assess_fault_tolerant_feasibility - Assess Fault-Tolerant Feasibility of an Algorithm Guided analysis: what would it take to run an algorithm (logical qubits × T count) fault-tolerantly, and is that worth it vs classical compute? Composes compute_fault_tolerant_resources and list_current_quantum_computers; the agent draws the conclusions and states the fit-spread caveat. Arguments: numLogicalQubits, tCount, qubitErrorRate
- compare_platforms - Compare Hardware Platforms for a Circuit Guided analysis: rank current hardware platforms for a given circuit and explain which constraint binds on each. Composes compare_hardware_scenarios and list_hardware_timings; the agent draws the conclusions. Arguments: numQubits, compDepth

## Metadata
- Owner: com.quantum-expectations
- Version: 0.3.0
- Runtime: Streamable Http
- Transports: HTTP
- License: Not captured
- Language: Not captured
- Stars: Not captured
- Updated: Jul 5, 2026
- Source: https://registry.modelcontextprotocol.io