Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Descripción del creador (original en inglés)
Signs, hash-chains, and verifies compute usage receipts via an MCP server, no issuer trust required.
Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.
Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.
Elige la app de IA que usas y copia la configuración.
Necesitas
¿Qué app usas?
Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.
Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json
{
"mcpServers": {
"computeledger": {
"command": "uvx",
"args": [
"computeledger-cli",
"computeledger",
"mcp"
]
}
}
}Ejecuta esto en tu terminal
claude mcp add computeledger -- uvx computeledger-cli computeledger mcpPégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"computeledger": {
"command": "uvx",
"args": [
"computeledger-cli",
"computeledger",
"mcp"
]
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Pégalo en .vscode/mcp.json de tu proyecto
{
"servers": {
"computeledger": {
"type": "stdio",
"command": "uvx",
"args": [
"computeledger-cli",
"computeledger",
"mcp"
]
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.
Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.
Esta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 7 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub RudrenduPaul, dueña del repo
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Este se ejecuta en tu computadora; no hay endpoint en internet
Se ejecuta en tu computadora y usa ajustes locales en su lugar
Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet
Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.
Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.
El registro no indica ninguna clave obligatoria, aunque algunos servidores te piden iniciar sesión la primera vez que los usas.
Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).
El repo de GitHub cambió por última vez –, y la última versión (0.1.3) llegó al registro hace 3 meses.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Python (uv) en tu computadora.
En la misma categoría: Spec Driven Development, Remote Desktop Commander, TF Rooms
Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.
Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Live room availability, rates and stay quotes for 12 New Leaf motels in Twin Falls, Idaho.
Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.
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.
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.
$ 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
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.
ledger verify detects, even if the tampered entry's own signature still looks locally valid.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.--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.computeledger run -- executes the wrapped command via an argument array, never a shell string, so metacharacters in the wrapped command are inert.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
| Flag | Meaning |
|---|---|
--local | Use ./.computeledger in the current directory instead of ~/.computeledger |
--json | Structured JSON on stdout instead of human-readable text |
--no-record-command | Omit the wrapped command string from the receipt (run only) |
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.
import { createReceipt, verifyReceipt, Ledger, verifyChain, loadKeyPair, resolvePaths } from "computeledger-cli";
from computeledger import create_receipt, verify_receipt, Ledger, verify_chain, load_key_pair
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.
| ComputeLedger | SkyPilot | OpenCost | AICert | |
|---|---|---|---|---|
| What it is | Signed, portable usage receipts | Multi-cloud job orchestration + cost | Kubernetes/cloud cost monitoring | Training-provenance attestation |
| Cryptographic verification | Yes (Ed25519, offline) | No | No | Yes (TPM-based) |
| Provider lock-in | None | Orchestrates specific clouds | Kubernetes/cloud-native | None |
| Tamper-evident history | Yes (hash-chained ledger) | No | No | No (single artifact, no chain) |
| GitHub stars | New | 10,441 | 6,659 (CNCF) | 20 |
| Project activity | Active | Active | Active | No commits since June 2024 |
Agent-native (MCP/--json) | Yes | Partial (API/SDK) | No | No |
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.
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.
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
Solo se muestra el principio; lee el resto en el repo