MCP server for modeling optimization problems as QUBO and solving them via IsingQ cloud with local validation and user confirmation.
Emerging. No concerning findings. Grades remain capped until the project builds reputation through adoption. Grades reflect the full trust pyramid: code, verification depth, and reputation. New projects cap at C until adoption is earned.
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ising-tech
Source: Glama
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ISINGQ_BASE_URLISINGQ_TIMEOUT_SECONDSTool annotations
6/10 tools have annotations
Add readOnlyHint or destructiveHint annotations to every tool so hosts can warn users before invoking.
All four hints declared on every tool
7/10 tools missing one or more hints — isingq_knowledge_get (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); isingq_modeling_guide_get (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); isingq_qubo_validate (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint), +4 more. OpenAI's directory rejects tools where any of the four hints are missing or non-boolean.
For every tool, set all four hints (readOnlyHint, destructiveHint, idempotentHint, openWorldHint) to explicit true/false values that match the handler’s actual behaviour.
Tool test coverage
7/10 tools referenced in tests (70%)
Write tests that reference each tool by name so every tool has at least one test.
Shell command execution
3 child_process/subprocess calls in production code — runs shell commands (src/hosts.js:126, packages/core/src/setup.js:69, packages/core/src/setup.js:88)
Prefer library functions over shell-outs. If you must shell out, ensure all inputs are properly escaped.
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