Skip to main content
Glama
systemone-decision-mcp

systemone-decision-mcp

by mhiqrambg

Related Servers

Alternatives to systemone-decision-mcp

No user-submitted related servers found.

    Related Servers

    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables 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
    • A
      license
      A
      quality
      A
      maintenance
      Enables Claude Code and other MCP clients to obtain fast, low-latency snap decisions — tool choice, option selection, and abstention when confidence is low — from a pluggable local decision engine such as Laya, Von, an Ollama chat model, or a custom provider. Engines can be swapped without changing the stable tools the client sees, with validation, per-attempt timeouts, confidence thresholds, and fallback chains handled by the server.
      3
      Apache 2.0
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables an agent to ask a System-1 decision engine which tool should answer a question, returning the winning choice with a confidence score, probability breakdown, and advice, plus a preset for routing code-structure questions and a generic mode for any user-supplied tool list.
      21 npm
      MIT
    • A
      license
      Not graded
      quality
      A
      maintenance
      Exposes 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.
      189 PyPI
      6
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables coding agents to make structured local decisions, choose bounded browser actions with approvals, and run coding workflows such as file relevance, context pruning, diff screening, and completion checks through MCP or CLI.
      Apache 2.0

    TDQS

    A3.6/5.0

    Scored across 8 tools

    Disambiguation4/5

    Most tools have clearly distinct purposes, but decide_tools, analyze_task, and check_tool_need all sit in the task-to-tool decision space and could require a moment to distinguish. The descriptions do clarify their scopes, keeping the overlap manageable rather than confusing.

    Naming Consistency5/5

    Every tool uses the same systemone_ prefix followed by a snake_case verb_noun pattern. Names such as decide_tools, recommend_skills, analyze_task, and refresh_catalog are predictable and consistent.

    Tool Count5/5

    Eight tools is well scoped for a decision/recommendation server, and each tool earns its place. There is no obvious filler or missing core operation from a count perspective.

    Completeness4/5

    The surface covers task analysis, tool and skill recommendation, single-tool checking, execution auditing, result evaluation, and catalog inspection/refresh. Minor gaps exist around managing settings or thresholds directly, but the key lifecycle is covered and intentional limitations are documented.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues