decision-lite
Related Servers
Alternatives to decision-lite
No user-submitted related servers found.
Related Servers
- AlicenseNot gradedqualityAmaintenanceEnables local typed decision-making over MCP Streamable HTTP, running Laya and Von models to turn arbitrary state into choice, score, and yes/no answers with probabilities.3Do What The F*ck You Want To Public
- AlicenseNot gradedqualityAmaintenanceExposes local MCP tools for typed, calibrated LLM decisions — gating risky actions, yes/no judging, classification, ordinal rating, and multi-question decisions in one pass. Runs on the model Devin's CLI already provides via ACP (or a fully offline local backend), so agents get calibrated confidence with no extra API key, no Ollama, and no waitlist.1MIT
- AlicenseAqualityBmaintenanceProvides agents with MCP tools for typed probabilistic decisions—Choice, Noul, and Score—with calibrated probabilities and abstention, using local OpenAI-compatible models via LM Studio logprobs.41MIT
- AlicenseNot gradedqualityAmaintenanceProvides an MCP interface to the Laya decision model, enabling typed queries (yes/no, multiple choice, score) with preflight token-budget reporting, honest confidence calibration, and structured error handling.128 PyPI1Apache 2.0
- AlicenseNot gradedqualityBmaintenanceEnables LLM agents to route responses as accept, verify, or ask-a-human based on token logprobs, and provides an MCP server for delegating generation to local models with confidence bands.MIT
- AlicenseNot gradedqualityAmaintenanceA lightweight, self-hostable MCP server for shared memory, structured command relay, and traceable decision evidence across AI runtimes.1MIT
TDQS
Scored across 3 tools
The three tools map cleanly to distinct phases: making a decision (evaluate), providing feedback (record_outcome), and inspecting calibration (decision_stats). There is no overlap in purpose and each has a clearly bounded role.
evaluate is a bare verb, record_outcome is verb_noun, and decision_stats is a noun phrase, so conventions are mixed. Each name is still readable and self-explanatory, but there is no single predictable pattern.
Three tools form a tight, complete decision-calibration loop with no filler. The count is well matched to the narrow stated purpose.
The evaluate/record_outcome/decision_stats cycle covers the core lifecycle of making, labeling, and auditing decisions. Minor gaps exist (e.g., no way to list or retrieve past evaluate calls), but essential workflows are covered.