原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
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Computeledger

作者:RudrenduPaul版本 0.1.3i★ –i在你的电脑上运行
注册名称io.github.RudrenduPaul/computeledger

安装

概览

作者提供的说明(英文原文)

Signs, hash-chains, and verifies compute usage receipts via an MCP server, no issuer trust required.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 其他

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 注册中心没有列出需要填写的密钥。

你需要

  • PyPI已安装 Python 的 uv(用于 uvx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "computeledger": {
      "command": "uvx",
      "args": [
        "computeledger-cli",
        "computeledger",
        "mcp"
      ]
    }
  }
}

在终端中运行这条命令

claude mcp add computeledger -- uvx computeledger-cli computeledger mcp

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "computeledger": {
      "command": "uvx",
      "args": [
        "computeledger-cli",
        "computeledger",
        "mcp"
      ]
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "computeledger": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "computeledger-cli",
        "computeledger",
        "mcp"
      ]
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 RudrenduPaul 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“其他”中的其他服务器比较i

  • 星标数多于此分类中其他 32623 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 32623 个服务器的 22% 更新
  • 基础检查结果等于或优于此分类中其他 32623 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Computeledger 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.1.3)于3个月前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Python (uv)。

有什么可以替代它?

同一分类中有:Spec Driven Development, Remote Desktop Commander, Draugr

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Spec Driven Development

作者:formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

在你的电脑上运行★ 440MIT14个月前更新
安装

Remote Desktop Commander

作者:desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

在云端运行★ 211前天更新
安装

Draugr

作者:draugr-dev

Security scanning for AI agents: SAST, SCA, secrets, IaC, DAST, ranked by real risk.

在你的电脑上运行今天更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

ComputeLedger

Install • Quickstart • Features • CLI reference • Comparison • FAQ

Sign, hash-chain, and independently verify compute usage, portable across any provider.

ComputeLedger records a compute job's usage (GPU-hours, hardware, duration, workload type) as a cryptographically signed receipt and appends it to a tamper-evident local ledger. Anyone can verify a receipt's authenticity and the ledger's integrity without trusting the issuer, and without buying into any single cloud, chain, or vendor's stack.

Install

npm install -g computeledger-cli
pip install computeledger-cli

Both packages install the same computeledger command. Receipts are interoperable either way: a receipt signed by the npm binary verifies correctly with the PyPI binary, and vice versa.

Quickstart

$ computeledger keys generate --local

Generated Ed25519 keypair. Public key: COxK/lkoWxWB42QKXjvcHnmBPozH4Oo2JHoOKDjsoU8= Private key: ./.computeledger/keys/ed25519.pem (mode 600)

$ computeledger record --local --provider aws --hardware nvidia-h100 \ --duration-seconds 3600 --gpu-hours 1 --workload-type training Recorded usage receipt 39952199-0897-48b8-92c5-e351f773c83d.

$ computeledger ledger verify --local Ledger valid: 1 entries, unbroken hash chain.

Or wrap a real job directly, no manual record call needed:

computeledger run --local --provider on-prem --hardware nvidia-a100 -- python train.py

run executes the wrapped command as a real subprocess (never through a shell), measures wall-clock duration, samples GPU utilization via nvidia-smi when one is present, and signs + appends the resulting receipt automatically. On a machine with no NVIDIA GPU, it still produces a duration-only receipt.

Give the receipt to anyone, on any machine, with no ComputeLedger account and no network call:

computeledger verify receipt.json

Why this exists

Multi-cloud and multi-provider GPU usage has no portable, verifiable record. A cost dashboard tells you what a provider says you used; it does not let a third party independently confirm that record wasn't altered after the fact, and it only works with the providers it integrates with. ComputeLedger is a lightweight, provider-agnostic attestation format: any process that can run a CLI command or call an MCP tool can produce a receipt, and any process, in any language, can verify one.

This is deliberately narrow. It does not compete with GPU marketplaces, cost dashboards, or confidential-computing platforms, all of which do real, different jobs. See the comparison below for exactly where the line is.

Features

  • Ed25519 signatures via Node's and Python's built-in/standard crypto libraries. No bespoke cryptography, no external crypto dependency on the TypeScript side.
  • Hash-chained ledger. Every receipt embeds the previous receipt's hash. Deleting, reordering, or editing a historical entry breaks the chain in a way ledger verify detects, even if the tampered entry's own signature still looks locally valid.
  • Cross-language interoperability by construction. A receipt signed by the npm package's computeledger binary verifies correctly against the PyPI package's computeledger binary. Both implementations serialize the receipt payload through the same deterministic canonical-JSON algorithm before hashing.
  • Provider-agnostic. No account, no API key, no dependency on any specific cloud or chain. Works identically on a laptop, an on-prem cluster, or any cloud VM.
  • Agent-native. Every subcommand supports --json for structured output, and computeledger mcp starts a Model Context Protocol server exposing record_usage, verify_receipt, list_ledger, and verify_ledger as callable tools.
  • No shell-injection surface. computeledger run -- executes the wrapped command via an argument array, never a shell string, so metacharacters in the wrapped command are inert.

CLI reference

computeledger keys generate [--local]

computeledger keys show [--local] [--json] computeledger run [--local] [--provider ] [--hardware ] [--workload-type training|inference|unknown] [--no-record-command] [--json] -- computeledger record --provider --hardware --duration-seconds [--gpu-hours ] [--flops ] [--workload-type ] [--local] [--json] computeledger verify [--json] computeledger ledger list [--local] [--json] computeledger ledger show [--local] [--json] computeledger ledger verify [--local] [--json] computeledger export --format json|csv [--out ] [--local] computeledger mcp

FlagMeaning
--localUse ./.computeledger in the current directory instead of ~/.computeledger
--jsonStructured JSON on stdout instead of human-readable text
--no-record-commandOmit the wrapped command string from the receipt (run only)

MCP Server

ComputeLedger ships a Model Context Protocol server so an AI agent (Claude, Cursor, or any MCP-compatible client) can record and verify compute usage receipts directly, without a human invoking the CLI by hand. The Python package exposes the server as a subcommand rather than a separate console script, so computeledger mcp is the real invocation, not computeledger-mcp.

pip install computeledger-cli

Add it to your MCP client's config (for Claude Desktop, claude_desktop_config.json):

{

"mcpServers": { "computeledger": { "command": "uvx", "args": ["--from", "computeledger-cli", "computeledger", "mcp"] } } }

The server exposes four tools, matching the CLI one-for-one:

  • record_usage(provider, hardware, durationSeconds, gpuHours?, estimatedFlops?, workloadType?, local?): signs a usage entry with the local Ed25519 key, appends it to the hash-chained ledger, and returns the signed receipt.
  • verify_receipt(receipt): independently verifies a receipt's signature and hash integrity.
  • list_ledger(local?): lists every receipt recorded in the local ledger.
  • verify_ledger(local?): verifies every entry's signature plus the unbroken hash chain across the whole ledger.

Example call:

record_usage(provider="lambda-labs", hardware="nvidia-h100", durationSeconds=3600, gpuHours=1, workloadType="training")

Transport is stdio, so there is nothing to host: the MCP client spawns the server as a local subprocess. Source: python/src/computeledger/mcp/server.py.

The npm package exposes the same four tools through the native TypeScript server (src/mcp/server.ts), invoked the same way with npx computeledger-cli mcp. Both implementations are cross-verified interoperable, and every tool returns the same structured JSON shape the CLI's --json mode produces.

Library API

import { createReceipt, verifyReceipt, Ledger, verifyChain, loadKeyPair, resolvePaths } from "computeledger-cli";
from computeledger import create_receipt, verify_receipt, Ledger, verify_chain, load_key_pair

Comparison

ComputeLedger occupies a narrow, specific gap: a portable, cryptographically verifiable usage receipt that doesn't require adopting any single provider's chain or platform. It is not trying to replace the tools below, each of which does a real, different job.

ComputeLedgerSkyPilotOpenCostAICert
What it isSigned, portable usage receiptsMulti-cloud job orchestration + costKubernetes/cloud cost monitoringTraining-provenance attestation
Cryptographic verificationYes (Ed25519, offline)NoNoYes (TPM-based)
Provider lock-inNoneOrchestrates specific cloudsKubernetes/cloud-nativeNone
Tamper-evident historyYes (hash-chained ledger)NoNoNo (single artifact, no chain)
GitHub starsNew10,4416,659 (CNCF)20
Project activityActiveActiveActiveNo commits since June 2024
Agent-native (MCP/--json)YesPartial (API/SDK)NoNo

SkyPilot and OpenCost solve real, adjacent problems (running jobs across clouds, and visualizing what they cost) at far larger scale and maturity than this project. Neither produces a signed, independently verifiable usage record. AICert attempted training-compute provenance as a standalone OSS tool using TPM-bound attestation and has had no commits since June 2024; ComputeLedger's scope is deliberately narrower (a usage receipt, not a full training-provenance framework) and ships both an npm and a PyPI package from day one specifically so the receipt format isn't locked to one language's ecosystem.

What is ComputeLedger, and why does it exist

ComputeLedger is an open-source CLI, library, and MCP server for producing and verifying cryptographically signed records of compute usage. It exists because compute usage claims (GPU-hours consumed, hardware used, workload duration) currently have no portable, offline-verifiable proof format: a billing dashboard is only as trustworthy as the provider issuing it, and it only covers that one provider. ComputeLedger's receipts are self-contained, signed JSON objects that any party, on any machine, in either of two independently maintained language implementations, can verify without a network call or a trusted third party.

FAQ

Does ComputeLedger require an account or API key? No. Everything runs locally. Keys are generated and stored on your own machine (~/.computeledger or ./.computeledger with --local).

Can a receipt be forged? Not without the private key used to sign it. verify recomputes the payload hash and checks the Ed25519 signature against the embedded public key; the public key itself is part of the signed payload, so substituting a different key changes the hash and invalidates the receipt.

What happens if there's no GPU? computeledger run degrades gracefully: it records wall-clock duration and whatever --hardware/--provider you specify, and simply omit

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