This is a mcp server for integrating Laya into your agentic workflow.
Laya MCP is an MCP server for Laya, a decision engine. Your LLM calls five tools with a structured question. Laya returns a label, a probability, or a score in one forward pass.
Claude Code / Copilot CLI: /plugin marketplace add NVentimiglia/laya-mcp then /plugin install laya@laya-mcp. Cursor: add git marketplace NVentimiglia/laya-mcp, then install laya. Skill-only install: npx skills add NVentimiglia/laya-mcp. Check the five tools without an IDE:
Variable Default Role --------- LAYAMODELID convaiinnovations/laya HuggingFace model LAYAMAXSTATETOKENS 512 Upper cap on state tokens LAYACONFIDENCETHRESHOLD 0.85 Automate vs escalate
Stable PyTorch stops at sm90 (RTX 4000). On Blackwell the server falls back to CPU (200 to 500 ms). Install the cu128 nightly (~3 GB) so the GPU kernels load:
--no-cache-dir stops pip from reusing an old wheel. Success prints tensor([4.], device='cuda:0'). torch.cuda.isavailable() can return True when kernels are missing.
Tool Use when ------ evaluatedecision Custom classification, scoring, or boolean check checkguardrails Before acting on user input routetask Light vs frontier model evaluateprdiff Before merge, review, or escalate moderatecontent Before publishing user-generated content
Your LLM calls a tool and acts on the typed result. Laya returns one of three shapes: choice (label + confidence + probabilities), noul (P(true) from 0.0 to 1.0), or score (expected value on an ordinal rubric). You can add questions to the same call without extra latency because they share one forward pass.
From the project README.
Add the radar badge to your README — it shows your project was picked up by MCP Radar and links to this page:
[](https://mcp.liqiwa.com/s/NVentimiglia--laya-mcp.html)
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