EMT Compute

com.emtcompute由 emtcompute.com 發布官方發布者v1.2.0更新於 Nov 6, 2026

GPU nodes and clusters, custom experiments, AI training and calculation reports for team workspaces.

已驗證Streamable HTTP可網頁執行雲端與基礎設施資料與分析AI 與機器學習

概覽

AI 產生的概覽

EMT Compute 讓助理瀏覽 GPU 報價、取得報價單、租用付費 GPU 節點或叢集，並查看工作區中的實驗與訓練工作。

可以做什麼
  • 瀏覽 GPU 報價、整機節點叢集、公開範本，以及附 CUDA 版本與連接埠的已驗證環境
  • 為單卡、叢集與實驗建立會到期的報價單，並列出科學實驗預設集
  • 啟動付費租用、叢集租用與實驗，或將工作掛接到既有叢集
  • 查看自有訂單、實驗工作、訓練工作、訓練配方與附指標的訓練事件
  • 讀取監控指標與生命週期狀態，取消實驗並終止租用
適用情境
適合讓助理比較 GPU 價格、準備並確認報價，接著在 EMT 工作區租用 GPU 或啟動科學運算、訓練工作，之後再查看結果與狀態。
執行需求
透過 streamable HTTP 連線至 emtcompute.com 遠端端點。需要 Authorization 標頭中的 bearer API 金鑰，且應在目標 EMT 工作區建立並只授予必要權限。租用另需額度、已接受的條款與明確的付費授權。個人資料、條款與工作區管理須在 EMT 主控台完成，無法透過 MCP 操作。
安裝前請注意
多個工具會產生實際費用：emt_rent、emt_rent_cluster 與 emt_start_experiment 會啟動付費租用，自動續租也可能在預算內追加租用時段。應先與使用者確認費用，保存啟動內容與冪等鍵，未確認釋放狀態前不要認為租用已停止。終止會刪除本機磁碟，保留的磁碟區與備份仍會計費。請使用限定範圍的金鑰，並只提供公開金鑰。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 EMT Compute，將其新增到工作區。
  2. 連接 Authorization token 憑證。它們會被私密儲存，絕不會在公開頁面上展示。
  3. 為需要使用其工具的對話啟用該服務。

Web executable，透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。

交給代理程式安裝

把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式，或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南，先向你展示發布者、端點和登入方式，經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。

閱讀 https://sourceweft.com/mcp/com.emtcompute%2Femt-compute/install.md，並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前，先告訴我它的發布者、端點和登入方式，等我確認。不要把 API 金鑰寫進命令或我會提交的檔案；問我金鑰應從哪裡取得。

檢視代理程式所依據的安裝指南

其他 MCP 客戶端

把它新增到你客戶端的 mcpServers 設定中。

{
  "mcpServers": {
    "emt-compute": {
      "type": "http",
      "url": "https://emtcompute.com/mcp",
      "headers": {
        "Authorization": "Bearer <YOUR_TOKEN>"
      }
    }
  }
}

工具

22

emt_catalog

Current GPU offers. Prices in EUR micro-units per GPU/hour; unknown metrics remain null. Paginated to keep responses small.

輸入參數limitmodeloffset

emt_clusters

Current whole-node cluster offers; fabric declarations do not establish independent EMT qualification.

無需輸入參數。

emt_templates

Public GPU container templates for ordinary rentals. Prefer emt_environments: public templates can be refused when their CUDA is newer than the node's driver.

無需輸入參數。

emt_environments

Verified environments (PyTorch, JAX, vLLM, TensorRT-LLM, ComfyUI, Unsloth) with their CUDA version and ports. Checked against the node before renting; they start an SSH server with the order's key.

無需輸入參數。

emt_experiment_presets

List scientific presets or inspect one preset's parameters, equations, methods and custom-input schema. Does not run a calculation.

輸入參數id

emt_orders

Owned GPU orders and lifecycle states. Requires read scope.

無需輸入參數。

emt_experiment_jobs

Owned experiment jobs, including reports and release state. Requires read scope.

無需輸入參數。

emt_experiment_job

Inspect an owned experiment and its authenticated result, output and calculation-report download links. Files are not sent into the model context.

輸入參數job必填

emt_training_jobs

List owned AI training jobs. Requires read scope; does not start training or rent GPUs.

無需輸入參數。

emt_training_job

Inspect an owned training job, its settings, lifecycle and recorded outcome.

輸入參數job必填

emt_training_recipe

Read the reproducible recipe for an owned training job, including model, dataset and training settings.

輸入參數job必填

emt_training_events

Read up to 100 training events with metrics, runtime and observed dataset hashes when recorded. For full history start after=0 and latest=false, then repeat with the greatest returned seq until an empty page. latest=true returns the most recent window only. Visible devices are not proof of GPU utilization.

輸入參數job必填afterlatest

emt_monitor

Metrics and lifecycle for an owned order. Missing telemetry is unknown.

輸入參數order必填

emt_quote

Create a fresh expiring GPU quote without renting or charging.

輸入參數node必填count必填hours必填

emt_cluster_quote

Quote selected whole nodes on one fabric without renting.

輸入參數hours必填nodes必填cluster必填

emt_experiment_quote

Quote 1–4 nodes for an experiment; hours × hourly gives the GPU rental ceiling in micro-EUR. Reserve is only an initial hold, not total cost.

輸入參數fp64nodecountmodelnodesminVrammaxMinutesenvironment

emt_rent

Start a PAID GPU rental with exactly one of environment (verified, from emt_environments: preferred) or template. Requires explicit spending authorization, fresh quote, rent scope, credit and accepted terms. Store payload and key before requesting.

輸入參數sshname必填portsquote必填setupvolumebackupsjupytertemplateenvironmentidempotency_key必填confirm_paid_rental必填

emt_rent_cluster

Start a PAID whole-node cluster rental. Public SSH key only. Confirm cost and fabric limits with the user first.

輸入參數ssh必填name必填quote必填idempotency_key必填confirm_paid_rental必填acknowledgeSlowNetwork

emt_start_experiment

Start a PAID scientific preset, customer script or command. Parameter sets distribute across quoted nodes; this does not automatically parallelize a single solver. Auto-continuation may rent additional segments up to its budget. Review all costs before confirming.

輸入參數sshautoname必填runs必填seedfileslevelconfigquotes必填resumeexperiment必填idempotency_key必填另有 1 個

emt_attach_cluster_experiment

Attach work to an already rented dedicated 2–4-node cluster. Does NOT start SSH remotely: run emt_cluster.py locally with the returned job ID and your private key. Whole cluster stops on completion/cancel; billing continues during preparation.

輸入參數sshname必填runs必填seedfileslevelconfigexperiment必填maxMinutesclusterOrder必填releaseCluster必填idempotency_key必填

emt_cancel_experiment

Cancel an owned experiment and request release of all its GPU nodes or attached cluster. Unfinished work can be lost. Recheck releasing until false.

輸入參數job必填confirm_stop必填

emt_terminate

Terminate every node in an owned rental. Local disks are deleted; retained volumes and backups remain billed. Inspect status until release is confirmed.

輸入參數order必填confirm_local_data_loss必填

版本歷史

4
  1. v1.2.0最新Nov 6, 2026
  2. v1.1.1Nov 5, 2026
  3. v1.1.0Nov 5, 2026
  4. v1.0.0Nov 4, 2026

評分

已滿足適用檢查項的 83%

該評分衡量此收錄條目的完整程度，依據註冊中心條目、端點與公開來源計算得出。它不是對伺服器本身的評價，也不表示伺服器安全或目前可用：可連通性是帶日期的檢查結果，評分也不包含安裝量或使用者評價。

  • 近 30 天內可連通必需25 分
  • 已宣告認證方式必需10 分
  • 已列出工具必需15 分
  • 描述必需15 分
  • 圖示10 分
  • 文件15 分

    請宣告包含 README 的 GitHub 儲存庫，或在 OAuth 受保護資源後設資料中提供 resource_documentation。

  • 授權條款不適用

    託管服務按其提供方的條款使用，因此這裡不要求授權條款。此檢查項不計入百分比。