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systemone-mcp

npm version npm downloads license: MIT node version

MCP server for any System One backend (Ollama nimble/tev/clef, TypeSafe jev, Kev, Laya).

Exposes two stdio tools:

  • systemone_evaluate — answer typed choice / score / noul questions with a System One model

  • systemone_list_models — list available System One models on the configured backend

Thin Zod-validated passthrough: MCP tools -> fetch({baseUrl}/v1/systemone) with optional Bearer key. model is a free-form non-empty string (never a hard-coded enum).

Run it with npx or bunx — see Install.

Env

Variable

Default

Notes

SYSTEMONE_BASE_URL

http://localhost:11434

Must start with http:// or https://. Ollama default http://localhost:11434.

SYSTEMONE_API_KEY

(unset)

Optional. TypeSafe cloud / Kev with key / Laya with LAYA_API_KEY. Sent as Authorization: Bearer <key>.

SYSTEMONE_MODEL

nimble

Default model when the tool call omits model. Any of nimble / tev / clef / jev / kev / laya.

See .env.example for a copy-paste starting point.

Related MCP server: Decision Bridge

Install

No build, no clone, no npm install — the published package ships prebuilt, so npx/bunx fetch a ready-to-run server.

npx -y @es11225599/systemone-mcp
bunx @es11225599/systemone-mcp

Requires Node >= 20 (or Bun). First run downloads the package; later runs are cached.

Run

Point any MCP client at the runner. Nothing to build or install locally:

{
  "mcpServers": {
    "system-one": {
      "command": "npx",
      "args": ["-y", "@es11225599/systemone-mcp"],
      "env": {
        "SYSTEMONE_BASE_URL": "http://localhost:11434",
        "SYSTEMONE_MODEL": "nimble"
      }
    }
  }
}

With Bun, swap the command and args:

{
  "mcpServers": {
    "system-one": {
      "command": "bunx",
      "args": ["@es11225599/systemone-mcp"],
      "env": {
        "SYSTEMONE_BASE_URL": "http://localhost:11434",
        "SYSTEMONE_MODEL": "nimble"
      }
    }
  }
}

Both forward stdio, so the server is fully wired either way. If your client resolves binaries through a shell, npx.cmd / bunx.cmd are the Windows equivalents.

Claude Code

claude mcp add system-one \
  -e SYSTEMONE_BASE_URL=http://localhost:11434 \
  -e SYSTEMONE_MODEL=nimble \
  -- npx -y @es11225599/systemone-mcp

From a clone (development)

npm install
npm run build
SYSTEMONE_BASE_URL=http://localhost:11434 node dist/index.js

Windows PowerShell:

npm install
npm run build
$env:SYSTEMONE_BASE_URL="http://localhost:11434"; node dist/index.js

npm run dev (tsx) skips the build for local iteration.

For TypeSafe cloud / Kev / Laya, add "SYSTEMONE_API_KEY": "<key>" to env and point SYSTEMONE_BASE_URL at that backend.

Manual parity

Direct HTTP check against an Ollama backend running nimble (bypasses MCP, same endpoint the server calls):

curl http://localhost:11434/v1/systemone \
  -H 'Content-Type: application/json' \
  -d '{"model":"nimble","state":"Our checkout has returned 500 errors since 9am.","questions":{"label":{"type":"choice","instructions":"Which label fits?","criteria":{"billing":"Payments","bug":"Errors","account":"Login"}}}}'

Expected: JSON with model, answers.label, and usage (input_tokens / output_tokens).

Available Tools

2 tools
systemone_evaluateC

Answer typed choice/score/noul questions with a System One model (jev/nimble/kev/tev/laya).

Inputs: state (required), questions (required), model, images, +1 more.

systemone_list_modelsB

List available System One models on the configured backend.

Inputs: no named parameters.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    TDQS

    B3.2/5.0

    Scored across 2 tools

    Disambiguation5/5

    The two tools serve clearly distinct purposes: one enumerates available models and the other runs an evaluation with a chosen model. There is no overlap in resource or action, so an agent cannot realistically confuse them.

    Naming Consistency4/5

    Both names share the 'systemone_' snake_case prefix, which is predictable and readable. The minor deviation is that 'evaluate' is a bare verb without a noun object unlike 'list_models', but the set still feels coherent.

    Tool Count3/5

    Two tools is thin even for a narrow evaluation-model domain; there is no separate model-detail, configuration, or result-retrieval tool. It is borderline rather than mismatched, since the core discover-then-evaluate flow is present.

    Completeness3/5

    The surface covers the minimal loop of listing models and evaluating a question, but lacks supporting operations such as fetching model metadata, setting backend configuration, or retrieving/batching prior evaluations. Agents can work around this only by relying on external configuration.

    Maintenance

    ActivityMaintained
    ResponsivenessNo recent community issues

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