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Quantum Suitability Validator

ojaskord/quantum-suitability-validator-mcp-server
authSTDIO, HTTPregistry active
Summary

This is a refusal-first triage engine that screens quantum computing proposals before budget gets allocated. It exposes quantum_assess_problem, which returns one of seven verdicts from RECOMMENDED_NOW through NOT_QUANTUM_AMENABLE, plus suitability score, problem class, dominant blockers, and hype language flags. The paid tier adds quantum_readiness_report with QUBO/Ising formulation guidance, hardware family fit for D-Wave/IBM/IonQ, error budget assessment, and classical baseline benchmarks. Reach for this when your agent needs to filter quantum POC requests against expert decision rules like QUBO failure patterns and penalty dominance before escalating to human committees. Part of Kord's validator suite that gates consequential actions.

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Quantum Suitability Validator MCP

ToolRank

MCP server that screens quantum computing POC proposals against expert decision rules -- before your agent escalates any initiative to a committee, allocates budget, or routes to a specialist.

What it does

Enterprise innovation agents and R&D workflow agents process backlogs of proposed technology initiatives tagged as potential quantum computing candidates. Before escalating any candidate to a human committee, allocating POC budget, or routing to a quantum specialist, the agent calls quantum_assess_problem to produce an auditable triage verdict.

This server is refusal-first by design. It downgrades or refuses more often than it approves. Every verdict is auditable and machine-readable.

Tools

quantum_assess_problem (Free: 5/month, no key required)

Screens a quantum computing proposal using an expert-validated four-dimensional scoring framework. Returns:

  • verdict: SCIENTIFICALLY_RECOMMENDED_NOW | COMMERCIALLY_RECOMMENDED_NOW | INVESTIGATE_FURTHER | PREMATURE | NOT_QUANTUM_AMENABLE
  • four_scores: scientific_fit (40% weight), hardware_feasibility (25%), advantage_potential (25%), commercial_relevance (10%), composite -- four independent 0.0-1.0 scores so a scientifically valid investigation is never confused with proven commercial advantage
  • advantage_claim_level: NONE | HYPOTHESISED | EXPERIMENTAL_SIGNAL | BENCHMARK_SUPPORTED | PRODUCTION_VALIDATED
  • suitability_score: 0.0-1.0 (equal to four_scores.composite)
  • confidence_score: 0.0-1.0
  • problem_class: combinatorial_optimisation | portfolio_optimisation | molecular_simulation | ml_kernel | cryptography_pqc | sampling_monte_carlo | other
  • dominant_blockers: specific reasons why the problem fails screening
  • hype_flags: detected hype language patterns
  • baseline_question: always "What is your classical baseline today, and what metric must improve for this to matter?"
  • next_best_action: specific actionable recommendation
  • agent_action: ESCALATE_TO_POC | ROUTE_TO_SIMULATOR | DEFINE_BASELINE_FIRST | REJECT | REQUEST_MORE_INFORMATION

quantum_readiness_report (Pro only)

Full auditable Quantum Readiness Report, weighted by audience profile (RESEARCH, ENTERPRISE, or INVESTOR -- the same problem legitimately scores differently by profile). Everything from quantum_assess_problem plus:

  • recommended_workflow: CLASSICAL_ONLY | HYBRID | SIMULATOR_ONLY | ANNEALING_PATH | GATE_MODEL_VARIATIONAL | INSUFFICIENT_INFORMATION
  • formulation_guidance: QUBO/Ising/variational suitability, estimated binary variables, penalty dominance risk
  • hardware_recommendations: hardware family fit scores with access routes (D-Wave Leap, IBM Cloud, IonQ Cloud)
  • error_budget_assessment: viability against current noise floors
  • classical_baseline_assessment: baseline strength and minimum benchmark requirement
  • validation_plan: ordered steps for technical review board submission
  • refusal_reason: populated when the report declines to recommend a path forward
  • commercial_reality_statement: populated for ENTERPRISE and INVESTOR profiles -- states plainly that production advantage over classical has not yet been broadly demonstrated

Connect

HTTP (Railway -- no install)

{"type": "http", "url": "https://quantum-suitability-validator-mcp-production.up.railway.app"}

stdio (npm -- requires ANTHROPIC_API_KEY)

npx quantum-suitability-validator-mcp

Harness Integration

Note: this server exposes tools at /mcp not the root URL.

Claude Code / Claude Desktop (.mcp.json)

{
  "mcpServers": {
    "quantum-suitability-validator": {
      "type": "http",
      "url": "https://quantum-suitability-validator-mcp-production.up.railway.app/mcp"
    }
  }
}

LangChain (Python)

from langchain_mcp_adapters.client import MultiServerMCPClient
client = MultiServerMCPClient({
    "quantum-suitability-validator": {
        "url": "https://quantum-suitability-validator-mcp-production.up.railway.app/mcp",
        "transport": "http"
    }
})
tools = await client.get_tools()

OpenAI Agents SDK (Python)

from agents import Agent, HostedMCPTool
agent = Agent(
    name="Assistant",
    tools=[HostedMCPTool(tool_config={
        "type": "mcp",
        "server_label": "quantum-suitability-validator",
        "server_url": "https://quantum-suitability-validator-mcp-production.up.railway.app/mcp",
        "require_approval": "never"
    })]
)

LangGraph

Same as LangChain above — langchain-mcp-adapters works with LangGraph natively.

Pricing

  • Free: 5 quantum_assess_problem calls/month per IP -- no API key required
  • Pro: $199/month -- unlimited quantum_assess_problem + full quantum_readiness_report
  • Enterprise: $499/month -- volume + SLA

Upgrade: kordagencies.com

Legal

AI-assisted triage -- NOT a substitute for experimental physicist review. Results are for informational and planning purposes only and do not constitute expert quantum computing advice. Full terms: kordagencies.com/terms.html

Kord Agencies Pte Ltd, Singapore

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Configuration

ANTHROPIC_API_KEY*secret

Anthropic API key for AI-powered quantum triage analysis

Registryactive
Packagequantum-suitability-validator-mcp
TransportSTDIO, HTTP
AuthRequired
UpdatedMay 4, 2026
View on GitHub

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