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walidboulanouar

jev-mcp

by walidboulanouar
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    Related Servers

    • jev-mcp

      henrykey
      A
      license
      Not graded
      quality
      B
      maintenance
      Exposes bounded TypeSafe Jev/System One decision primitives as MCP tools, enabling agents to make choices, scores, yes/no judgments, and batched decisions over remote HTTPS with shared state.
      MIT

    • jevjam

      beremaran
      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

    • mcp-jev

      Chrishow2
      A
      license
      Not graded
      quality
      B
      maintenance
      Enables MCP clients to get machine-readable yes/no, choice, and score decisions from TypeSafe Jev, bridging fast classification to Cursor and other clients.
      MIT

    • use-jev

      silkyland
      A
      license
      Not graded
      quality
      C
      maintenance
      Enables MCP-capable agents to run TypeSafe's Jev judgment model as typed yes/no, choice, and score tools, with calibrated probabilities, confidence thresholds, escalation for uncertain or non-judgment tasks, and an optional action gate that fails open.
      1
      MIT

    • jev_mcp

      wr0x00
      A
      license
      Not graded
      quality
      B
      maintenance
      Provides MCP tools that wrap Jev's finite typed judgments to give agents a semantic decision-control layer for task routing, pre-execution risk gating, and completion verification, keeping final execution authority in code.
      MIT

    • decision-lite

      cckyros
      A
      license
      A
      quality
      C
      maintenance
      An MCP server that answers typed noul/choice/score questions about a given state with probability distributions and confidence, for routing, escalation, and gating decisions. It runs on pluggable backends (local Needle 3 or Laya models, or any OpenAI-compatible endpoint) and logs every decision so recorded ground truth can be used to track calibration.
      3
      MIT

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    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

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