subq-snap-mcp
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Alternatives to subq-snap-mcp
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- AlicenseNot gradedqualityCmaintenanceEnables structured yes/no, multiple-choice, and ordered-score judgments from supplied text and criteria, returning typed probabilities, selected labels, scores, and confidence. It exposes bounded decision tools without search, chat generation, arbitrary HTTP requests, or action execution.0MIT
- AlicenseNot gradedqualityCmaintenanceEnables agents to evaluate single records or batches with dynamically authored typed questions, returning structured decisions and probabilities.25 PyPIMIT
- AlicenseAqualityAmaintenanceEnables MCP clients to classify, score, and evaluate content with structured typed decisions via a single generic tool.115 npm2MIT
- AlicenseNot gradedqualityAmaintenanceEnables agents and services to ask small decision models typed questions about text, JSON, images, or video, returning labels, scores, or yes/no answers over MCP tools or a Jev-compatible HTTP API.Apache 2.0
- AlicenseNot gradedqualityAmaintenanceLets MCP clients ask typed questions — yes/no, choice, or score — about structured state, including images, and receive calibrated probabilities from System One decision models such as TypeSafe Jev and Cloudflare Clef. Supports TypeSafe, OpenRouter, and local providers selectable per request, with input validation and cost reporting.0MIT
- AlicenseAqualityDmaintenanceEnables agents to perform typed judgments—classify, score, check, match, and screen—over closed answer sets with confidence scores, without text generation.725MIT
TDQS
Scored across 5 tools
The three single-type tools target distinct question types, but snap_decide is effectively a superset that can also answer choice, score, or noul questions. The descriptions clarify the single-vs-multi-question distinction, but this overlap leaves some room for misselection.
All tools share the snap_ prefix and use consistent snake_case verb/noun naming, such as snap_choice, snap_score, and snap_list_models. The domain term noul is unusual but used consistently as a question type.
With only five tools, the surface is tightly scoped to the decision-model purpose: one general multi-question tool, three single-question conveniences, and model discovery. There is no tool bloat and the set stays easy to scan.
The set covers the core decision primitives (choice, score, noul), multi-question calls, and listing available models. Minor gaps exist around batch evaluation across multiple states or richer model metadata, but the main workflows are covered.